if (!require("remotes"))
install.packages("remotes")
remotes::install_github("flavjack/inti")Impact of Interstock and Rootstock on the Vigor and Productive Development of Mango (Mangifera indica L.) in the San Lorenzo Valley, Piura, Peru
1 Project Setup
Install inti development version.
library(emmeans)
library(corrplot)
library(multcomp)
library(FSA)
library(factoextra)
library(corrplot)
source('https://inkaverse.com/setup.r')
cat("Project: ", getwd(), "\n")Project: C:/INIA/GIT/prochira_injertos
session_info()─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.4.1 (2024-06-14 ucrt)
os Windows 11 x64 (build 22631)
system x86_64, mingw32
ui RTerm
language (EN)
collate Spanish_Peru.utf8
ctype Spanish_Peru.utf8
tz America/Lima
date 2024-10-01
pandoc 3.2 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
─ Packages ───────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
agricolae 1.3-7 2023-10-22 [1] CRAN (R 4.4.0)
AlgDesign 1.2.1 2022-05-25 [1] CRAN (R 4.4.0)
askpass 1.2.0 2023-09-03 [1] CRAN (R 4.4.0)
boot 1.3-30 2024-02-26 [2] CRAN (R 4.4.1)
cachem 1.1.0 2024-05-16 [1] CRAN (R 4.4.0)
cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.4.0)
cli 3.6.2 2023-12-11 [1] CRAN (R 4.4.0)
cluster 2.1.6 2023-12-01 [2] CRAN (R 4.4.1)
coda 0.19-4.1 2024-01-31 [1] CRAN (R 4.4.0)
codetools 0.2-20 2024-03-31 [2] CRAN (R 4.4.1)
colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.4.0)
corrplot * 0.92 2021-11-18 [1] CRAN (R 4.4.0)
cowplot * 1.1.3 2024-01-22 [1] CRAN (R 4.4.0)
curl 5.2.1 2024-03-01 [1] CRAN (R 4.4.0)
devtools * 2.4.5 2022-10-11 [1] CRAN (R 4.4.0)
digest 0.6.35 2024-03-11 [1] CRAN (R 4.4.0)
dplyr * 1.1.4 2023-11-17 [1] CRAN (R 4.4.0)
DT 0.33 2024-04-04 [1] CRAN (R 4.4.0)
ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.4.0)
emmeans * 1.10.2 2024-05-20 [1] CRAN (R 4.4.0)
estimability 1.5.1 2024-05-12 [1] CRAN (R 4.4.0)
evaluate 0.23 2023-11-01 [1] CRAN (R 4.4.0)
factoextra * 1.0.7 2020-04-01 [1] CRAN (R 4.4.0)
FactoMineR * 2.11 2024-04-20 [1] CRAN (R 4.4.0)
fansi 1.0.6 2023-12-08 [1] CRAN (R 4.4.0)
fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.4.0)
flashClust 1.01-2 2012-08-21 [1] CRAN (R 4.4.0)
forcats * 1.0.0 2023-01-29 [1] CRAN (R 4.4.0)
fs 1.6.4 2024-04-25 [1] CRAN (R 4.4.0)
FSA * 0.9.5 2023-08-26 [1] CRAN (R 4.4.0)
gargle 1.5.2 2023-07-20 [1] CRAN (R 4.4.0)
generics 0.1.3 2022-07-05 [1] CRAN (R 4.4.0)
ggplot2 * 3.5.1 2024-04-23 [1] CRAN (R 4.4.0)
ggrepel 0.9.5 2024-01-10 [1] CRAN (R 4.4.0)
glue 1.7.0 2024-01-09 [1] CRAN (R 4.4.0)
googledrive * 2.1.1 2023-06-11 [1] CRAN (R 4.4.0)
googlesheets4 * 1.1.1 2023-06-11 [1] CRAN (R 4.4.0)
gsheet * 0.4.5 2020-04-07 [1] CRAN (R 4.4.0)
gtable 0.3.5 2024-04-22 [1] CRAN (R 4.4.0)
hms 1.1.3 2023-03-21 [1] CRAN (R 4.4.0)
htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.4.0)
htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.4.0)
httpuv 1.6.15 2024-03-26 [1] CRAN (R 4.4.0)
httr 1.4.7 2023-08-15 [1] CRAN (R 4.4.0)
huito * 0.2.4 2023-10-25 [1] CRAN (R 4.4.0)
inti * 0.6.5 2024-08-02 [1] Github (flavjack/inti@38be898)
jsonlite 1.8.8 2023-12-04 [1] CRAN (R 4.4.0)
knitr * 1.46 2024-04-06 [1] CRAN (R 4.4.0)
later 1.3.2 2023-12-06 [1] CRAN (R 4.4.0)
lattice 0.22-6 2024-03-20 [2] CRAN (R 4.4.1)
leaps 3.1 2020-01-16 [1] CRAN (R 4.4.0)
lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.4.0)
lme4 1.1-35.3 2024-04-16 [1] CRAN (R 4.4.0)
lubridate * 1.9.3 2023-09-27 [1] CRAN (R 4.4.0)
magick * 2.8.3 2024-02-18 [1] CRAN (R 4.4.0)
magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.4.0)
MASS * 7.3-60.2 2024-04-26 [2] CRAN (R 4.4.1)
Matrix 1.7-0 2024-04-26 [2] CRAN (R 4.4.1)
memoise 2.0.1 2021-11-26 [1] CRAN (R 4.4.0)
mime 0.12 2021-09-28 [1] CRAN (R 4.4.0)
miniUI 0.1.1.1 2018-05-18 [1] CRAN (R 4.4.0)
minqa 1.2.7 2024-05-20 [1] CRAN (R 4.4.0)
mnormt 2.1.1 2022-09-26 [1] CRAN (R 4.4.0)
multcomp * 1.4-25 2023-06-20 [1] CRAN (R 4.4.0)
multcompView 0.1-10 2024-03-08 [1] CRAN (R 4.4.0)
munsell 0.5.1 2024-04-01 [1] CRAN (R 4.4.0)
mvtnorm * 1.2-5 2024-05-21 [1] CRAN (R 4.4.0)
nlme 3.1-164 2023-11-27 [2] CRAN (R 4.4.1)
nloptr 2.0.3 2022-05-26 [1] CRAN (R 4.4.0)
openssl 2.2.0 2024-05-16 [1] CRAN (R 4.4.0)
pillar 1.9.0 2023-03-22 [1] CRAN (R 4.4.0)
pkgbuild 1.4.4 2024-03-17 [1] CRAN (R 4.4.0)
pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.4.0)
pkgload 1.3.4 2024-01-16 [1] CRAN (R 4.4.0)
profvis 0.3.8 2023-05-02 [1] CRAN (R 4.4.0)
promises 1.3.0 2024-04-05 [1] CRAN (R 4.4.0)
psych * 2.4.3 2024-03-18 [1] CRAN (R 4.4.0)
purrr * 1.0.2 2023-08-10 [1] CRAN (R 4.4.0)
R6 2.5.1 2021-08-19 [1] CRAN (R 4.4.0)
rappdirs 0.3.3 2021-01-31 [1] CRAN (R 4.4.0)
Rcpp 1.0.12 2024-01-09 [1] CRAN (R 4.4.0)
readr * 2.1.5 2024-01-10 [1] CRAN (R 4.4.0)
remotes 2.5.0 2024-03-17 [1] CRAN (R 4.4.0)
rlang 1.1.3 2024-01-10 [1] CRAN (R 4.4.0)
rmarkdown 2.27 2024-05-17 [1] CRAN (R 4.4.0)
rstudioapi 0.16.0 2024-03-24 [1] CRAN (R 4.4.0)
sandwich 3.1-0 2023-12-11 [1] CRAN (R 4.4.0)
scales 1.3.0 2023-11-28 [1] CRAN (R 4.4.0)
scatterplot3d 0.3-44 2023-05-05 [1] CRAN (R 4.4.0)
sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.4.0)
shiny * 1.8.1.1 2024-04-02 [1] CRAN (R 4.4.0)
showtext 0.9-7 2024-03-02 [1] CRAN (R 4.4.0)
showtextdb 3.0 2020-06-04 [1] CRAN (R 4.4.0)
stringi 1.8.4 2024-05-06 [1] CRAN (R 4.4.0)
stringr * 1.5.1 2023-11-14 [1] CRAN (R 4.4.0)
survival * 3.6-4 2024-04-24 [2] CRAN (R 4.4.1)
sysfonts 0.8.9 2024-03-02 [1] CRAN (R 4.4.0)
TH.data * 1.1-2 2023-04-17 [1] CRAN (R 4.4.0)
tibble * 3.2.1 2023-03-20 [1] CRAN (R 4.4.0)
tidyr * 1.3.1 2024-01-24 [1] CRAN (R 4.4.0)
tidyselect 1.2.1 2024-03-11 [1] CRAN (R 4.4.0)
tidyverse * 2.0.0 2023-02-22 [1] CRAN (R 4.4.0)
timechange 0.3.0 2024-01-18 [1] CRAN (R 4.4.0)
tzdb 0.4.0 2023-05-12 [1] CRAN (R 4.4.0)
urlchecker 1.0.1 2021-11-30 [1] CRAN (R 4.4.0)
usethis * 2.2.3 2024-02-19 [1] CRAN (R 4.4.0)
utf8 1.2.4 2023-10-22 [1] CRAN (R 4.4.0)
vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.4.0)
withr 3.0.1 2024-07-31 [1] CRAN (R 4.4.1)
xfun 0.44 2024-05-15 [1] CRAN (R 4.4.0)
xtable 1.8-4 2019-04-21 [1] CRAN (R 4.4.0)
yaml 2.3.8 2023-12-11 [1] CRAN (R 4.4.0)
zoo 1.8-12 2023-04-13 [1] CRAN (R 4.4.0)
[1] C:/Users/INIA/AppData/Local/R/win-library/4.4
[2] C:/Program Files/R/R-4.4.1/library
──────────────────────────────────────────────────────────────────────────────
2 Import data
Data were imported from the field book evaluated during the 2017-2019 growing seasons. The evaluations focused on the agronomic traits and fruit biometrics of the mango crop.
url <- "https://docs.google.com/spreadsheets/d/1E_cUmiRFoPLGAj7AQC6HZBD6hXtqzg2UHPvtWr2QR_U/edit#gid=2112492836"
gs <- url %>%
as_sheets_id()
ley <- gs %>%
range_read("leyenda") %>%
rename(tratamientos = TRATAM) %>%
rename_with(~ tolower(.))
rdt <- gs %>%
range_read("db") %>%
merge(., ley) %>%
dplyr::select(year = "año", n, tratamientos,n_trat:yema, everything()) %>%
rename(treat = tratamientos
, n_treat = n_trat
, block = bloque
, n_plant = n_planta
, height = alt_planta
, n_fruits = n_frutos
, flowering = per_floracion
, sproud = per_brote
, scion = yema
, stock = patron
, edge = puente
) %>%
dplyr::arrange(year, n, treat) %>%
mutate(across(year:n_plant, ~ as.factor(.)))
glimpse(rdt)
## Rows: 648
## Columns: 13
## $ year <fct> 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, …
## $ n <fct> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1…
## $ treat <fct> 141, 141, 141, 141, 141, 141, 141, 141, 141, 231, 231, 231, …
## $ n_treat <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 8, 8, …
## $ stock <fct> CHULUCANAS, CHULUCANAS, CHULUCANAS, CHULUCANAS, CHULUCANAS, …
## $ edge <fct> CHULUCANAS, CHULUCANAS, CHULUCANAS, CHULUCANAS, CHULUCANAS, …
## $ scion <fct> KENT, KENT, KENT, KENT, KENT, KENT, KENT, KENT, KENT, KENT, …
## $ block <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
## $ n_plant <fct> 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, …
## $ height <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ n_fruits <dbl> 170, 200, 310, NA, 235, 185, 180, 132, 80, 231, 198, 195, 20…
## $ flowering <dbl> 60, 50, 50, NA, 80, 60, 40, 90, 90, 60, 70, 40, 90, 80, 80, …
## $ sproud <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
fru <- gs %>%
range_read("db_frutos") %>%
merge(., ley, ) %>%
dplyr::select(year = "año", n, tratamientos,n_trat:yema, everything()) %>%
rename(treat = tratamientos
, n_treat = n_trat
, block = bloque
, n_plant = n_planta
, weigth = peso
, long = largo
, n_fruits = n_frutos
, diameter_1 = diametro_1
, diameter_2 = diametro_2
, sample = muestra
, scion = yema
, stock = patron
, edge = puente
) %>%
dplyr::arrange(year, n, treat) %>%
mutate(diameter_average = (diameter_1 + diameter_2)/2) %>%
mutate(across(year:sample, ~ as.factor(.)))
glimpse(fru)
## Rows: 240
## Columns: 16
## $ year <fct> 2023, 2023, 2023, 2023, 2023, 2023, 2023, 2023, 2023,…
## $ n <fct> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16…
## $ treat <fct> 141, 141, 141, 141, 141, 141, 141, 141, 141, 141, 231…
## $ n_treat <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ stock <fct> CHULUCANAS, CHULUCANAS, CHULUCANAS, CHULUCANAS, CHULU…
## $ edge <fct> CHULUCANAS, CHULUCANAS, CHULUCANAS, CHULUCANAS, CHULU…
## $ scion <fct> KENT, KENT, KENT, KENT, KENT, KENT, KENT, KENT, KENT,…
## $ block <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ n_plant <fct> 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2,…
## $ sample <fct> 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3,…
## $ n_fruits <dbl> 26, 26, 26, 26, 26, 35, 35, 35, 35, 35, 118, 118, 118…
## $ weigth <dbl> 270, 520, 385, 230, 285, 600, 457, 520, 665, 305, 422…
## $ long <dbl> 86, 111, 103, 86, 88, 116, 101, 115, 126, 91, 100, 10…
## $ diameter_1 <dbl> 78, 90, 86, 70, 78, 96, 88, 88, 103, 78, 91, 84, 84, …
## $ diameter_2 <dbl> 74, 83, 75, 69, 71, 87, 88, 81, 95, 80, 83, 76, 72, 8…
## $ diameter_average <dbl> 76.0, 86.5, 80.5, 69.5, 74.5, 91.5, 88.0, 84.5, 99.0,…ley %>% kable(caption = "Interstock grafting treatments", align = 'c')| n_trat | tratamientos | patron | puente | yema |
|---|---|---|---|---|
| 1 | 141 | CHULUCANAS | CHULUCANAS | KENT |
| 2 | 231 | CHATO | JULIE | KENT |
| 3 | 241 | CHULUCANAS | CHATO | KENT |
| 4 | 211 | CHATO | IRWIN | KENT |
| 5 | 131 | CHULUCANAS | JULIE | KENT |
| 6 | 111 | CHULUCANAS | IRWIN | KENT |
| 7 | 221 | CHATO | CHATO | KENT |
| 8 | 121 | CHATO | CHULUCANAS | KENT |
rdt %>% kable(caption = "Evaluation of the agronomic characteristics of mango", align = 'c')| year | n | treat | n_treat | stock | edge | scion | block | n_plant | height | n_fruits | flowering | sproud |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017 | 1 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 1 | 170 | 60 | ||
| 2017 | 2 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 2 | 200 | 50 | ||
| 2017 | 3 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 3 | 310 | 50 | ||
| 2017 | 4 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 4 | ||||
| 2017 | 5 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 5 | 235 | 80 | ||
| 2017 | 6 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 6 | 185 | 60 | ||
| 2017 | 7 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 7 | 180 | 40 | ||
| 2017 | 8 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 8 | 132 | 90 | ||
| 2017 | 9 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 9 | 80 | 90 | ||
| 2017 | 10 | 231 | 2 | CHATO | JULIE | KENT | 1 | 1 | 231 | 60 | ||
| 2017 | 11 | 231 | 2 | CHATO | JULIE | KENT | 1 | 2 | 198 | 70 | ||
| 2017 | 12 | 231 | 2 | CHATO | JULIE | KENT | 1 | 3 | 195 | 40 | ||
| 2017 | 13 | 231 | 2 | CHATO | JULIE | KENT | 1 | 4 | 200 | 90 | ||
| 2017 | 14 | 231 | 2 | CHATO | JULIE | KENT | 1 | 5 | 180 | 80 | ||
| 2017 | 15 | 231 | 2 | CHATO | JULIE | KENT | 1 | 6 | 140 | 80 | ||
| 2017 | 16 | 231 | 2 | CHATO | JULIE | KENT | 1 | 7 | 200 | 60 | ||
| 2017 | 17 | 231 | 2 | CHATO | JULIE | KENT | 1 | 8 | 186 | 75 | ||
| 2017 | 18 | 231 | 2 | CHATO | JULIE | KENT | 1 | 9 | ||||
| 2017 | 19 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 1 | ||||
| 2017 | 20 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 2 | 165 | 75 | ||
| 2017 | 21 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 3 | 210 | 75 | ||
| 2017 | 22 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 4 | 201 | 80 | ||
| 2017 | 23 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 5 | 110 | 80 | ||
| 2017 | 24 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 6 | 215 | 90 | ||
| 2017 | 25 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 7 | 200 | 80 | ||
| 2017 | 26 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 8 | 160 | 80 | ||
| 2017 | 27 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 9 | 162 | 75 | ||
| 2017 | 28 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 1 | 204 | 70 | ||
| 2017 | 29 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 2 | 124 | 80 | ||
| 2017 | 30 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 3 | 130 | 80 | ||
| 2017 | 31 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 4 | 6 | 5 | ||
| 2017 | 32 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 5 | 90 | 35 | ||
| 2017 | 33 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 6 | 170 | 60 | ||
| 2017 | 34 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 7 | 165 | 45 | ||
| 2017 | 35 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 8 | 100 | 25 | ||
| 2017 | 36 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 9 | 70 | 25 | ||
| 2017 | 37 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 1 | 75 | 80 | ||
| 2017 | 38 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 2 | 200 | 80 | ||
| 2017 | 39 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 3 | 184 | 80 | ||
| 2017 | 40 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 4 | 102 | 70 | ||
| 2017 | 41 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 5 | 190 | 60 | ||
| 2017 | 42 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 6 | 180 | 70 | ||
| 2017 | 43 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 7 | 175 | 75 | ||
| 2017 | 44 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 8 | 120 | 80 | ||
| 2017 | 45 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 9 | 155 | 60 | ||
| 2017 | 46 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 1 | 230 | 90 | ||
| 2017 | 47 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 2 | 110 | 90 | ||
| 2017 | 48 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 3 | 185 | 90 | ||
| 2017 | 49 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 4 | 220 | 90 | ||
| 2017 | 50 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 5 | 180 | 90 | ||
| 2017 | 51 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 6 | 175 | 60 | ||
| 2017 | 52 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 7 | 210 | 90 | ||
| 2017 | 53 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 8 | 180 | 90 | ||
| 2017 | 54 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 9 | 178 | 90 | ||
| 2017 | 55 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 1 | 150 | 90 | ||
| 2017 | 56 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 2 | 160 | 85 | ||
| 2017 | 57 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 3 | 200 | 90 | ||
| 2017 | 58 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 4 | 140 | 90 | ||
| 2017 | 59 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 5 | 175 | 90 | ||
| 2017 | 60 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 6 | 200 | 80 | ||
| 2017 | 61 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 7 | 208 | 90 | ||
| 2017 | 62 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 8 | 300 | 90 | ||
| 2017 | 63 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 9 | 230 | 90 | ||
| 2017 | 64 | 221 | 7 | CHATO | CHATO | KENT | 1 | 1 | 190 | 90 | ||
| 2017 | 65 | 221 | 7 | CHATO | CHATO | KENT | 1 | 2 | 206 | 90 | ||
| 2017 | 66 | 221 | 7 | CHATO | CHATO | KENT | 1 | 3 | 145 | 80 | ||
| 2017 | 67 | 221 | 7 | CHATO | CHATO | KENT | 1 | 4 | 51 | 20 | ||
| 2017 | 68 | 221 | 7 | CHATO | CHATO | KENT | 1 | 5 | 45 | 30 | ||
| 2017 | 69 | 221 | 7 | CHATO | CHATO | KENT | 1 | 6 | 163 | 80 | ||
| 2017 | 70 | 221 | 7 | CHATO | CHATO | KENT | 1 | 7 | 35 | 15 | ||
| 2017 | 71 | 221 | 7 | CHATO | CHATO | KENT | 1 | 8 | 200 | 80 | ||
| 2017 | 72 | 221 | 7 | CHATO | CHATO | KENT | 1 | 9 | 32 | 15 | ||
| 2017 | 73 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 1 | 170 | 90 | ||
| 2017 | 74 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 2 | 350 | 80 | ||
| 2017 | 75 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 3 | 200 | 90 | ||
| 2017 | 76 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 4 | 154 | 70 | ||
| 2017 | 77 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 5 | 180 | 90 | ||
| 2017 | 78 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 6 | 130 | 90 | ||
| 2017 | 79 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 7 | 145 | 90 | ||
| 2017 | 80 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 8 | 130 | 90 | ||
| 2017 | 81 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 9 | 220 | 90 | ||
| 2017 | 82 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 1 | 223 | 90 | ||
| 2017 | 83 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 2 | 220 | 90 | ||
| 2017 | 84 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 3 | 230 | 90 | ||
| 2017 | 85 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 4 | 200 | 90 | ||
| 2017 | 86 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 5 | 210 | 90 | ||
| 2017 | 87 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 6 | 150 | 90 | ||
| 2017 | 88 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 7 | 220 | 80 | ||
| 2017 | 89 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 8 | 270 | 90 | ||
| 2017 | 90 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 9 | 170 | 85 | ||
| 2017 | 91 | 231 | 2 | CHATO | JULIE | KENT | 2 | 1 | 28 | 90 | ||
| 2017 | 92 | 231 | 2 | CHATO | JULIE | KENT | 2 | 2 | 250 | 90 | ||
| 2017 | 93 | 231 | 2 | CHATO | JULIE | KENT | 2 | 3 | 115 | 70 | ||
| 2017 | 94 | 231 | 2 | CHATO | JULIE | KENT | 2 | 4 | 160 | 80 | ||
| 2017 | 95 | 231 | 2 | CHATO | JULIE | KENT | 2 | 5 | 200 | 90 | ||
| 2017 | 96 | 231 | 2 | CHATO | JULIE | KENT | 2 | 6 | 150 | 90 | ||
| 2017 | 97 | 231 | 2 | CHATO | JULIE | KENT | 2 | 7 | 120 | 90 | ||
| 2017 | 98 | 231 | 2 | CHATO | JULIE | KENT | 2 | 8 | 230 | 90 | ||
| 2017 | 99 | 231 | 2 | CHATO | JULIE | KENT | 2 | 9 | 240 | 80 | ||
| 2017 | 100 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 1 | 210 | 80 | ||
| 2017 | 101 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 2 | 205 | 90 | ||
| 2017 | 102 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 3 | 210 | 90 | ||
| 2017 | 103 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 4 | 170 | 80 | ||
| 2017 | 104 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 5 | 120 | 80 | ||
| 2017 | 105 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 6 | 240 | 90 | ||
| 2017 | 106 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 7 | 280 | 90 | ||
| 2017 | 107 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 8 | 260 | 90 | ||
| 2017 | 108 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 9 | 170 | 70 | ||
| 2017 | 109 | 221 | 7 | CHATO | CHATO | KENT | 2 | 1 | 142 | 90 | ||
| 2017 | 110 | 221 | 7 | CHATO | CHATO | KENT | 2 | 2 | 120 | 90 | ||
| 2017 | 111 | 221 | 7 | CHATO | CHATO | KENT | 2 | 3 | 140 | 90 | ||
| 2017 | 112 | 221 | 7 | CHATO | CHATO | KENT | 2 | 4 | 180 | 90 | ||
| 2017 | 113 | 221 | 7 | CHATO | CHATO | KENT | 2 | 5 | 160 | 90 | ||
| 2017 | 114 | 221 | 7 | CHATO | CHATO | KENT | 2 | 6 | 130 | 90 | ||
| 2017 | 115 | 221 | 7 | CHATO | CHATO | KENT | 2 | 7 | 70 | 90 | ||
| 2017 | 116 | 221 | 7 | CHATO | CHATO | KENT | 2 | 8 | 115 | 90 | ||
| 2017 | 117 | 221 | 7 | CHATO | CHATO | KENT | 2 | 9 | 104 | 90 | ||
| 2017 | 118 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 1 | ||||
| 2017 | 119 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 2 | 208 | 90 | ||
| 2017 | 120 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 3 | 110 | 90 | ||
| 2017 | 121 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 4 | 140 | 90 | ||
| 2017 | 122 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 5 | 108 | 80 | ||
| 2017 | 123 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 6 | 120 | 90 | ||
| 2017 | 124 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 7 | 250 | 90 | ||
| 2017 | 125 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 8 | 220 | 90 | ||
| 2017 | 126 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 9 | 235 | 80 | ||
| 2017 | 127 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 1 | 170 | 80 | ||
| 2017 | 128 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 2 | 182 | 80 | ||
| 2017 | 129 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 3 | 148 | 90 | ||
| 2017 | 130 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 4 | 160 | 90 | ||
| 2017 | 131 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 5 | 23 | 25 | ||
| 2017 | 132 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 6 | 175 | 80 | ||
| 2017 | 133 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 7 | 227 | 90 | ||
| 2017 | 134 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 8 | 180 | 90 | ||
| 2017 | 135 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 9 | 50 | 90 | ||
| 2017 | 136 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 1 | 180 | 80 | ||
| 2017 | 137 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 2 | 240 | 90 | ||
| 2017 | 138 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 3 | 124 | 70 | ||
| 2017 | 139 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 4 | 220 | 85 | ||
| 2017 | 140 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 5 | 240 | 80 | ||
| 2017 | 141 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 6 | 90 | 80 | ||
| 2017 | 142 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 7 | 220 | 85 | ||
| 2017 | 143 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 8 | 250 | 90 | ||
| 2017 | 144 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 9 | 174 | 90 | ||
| 2017 | 145 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 1 | 170 | 85 | ||
| 2017 | 146 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 2 | 198 | 80 | ||
| 2017 | 147 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 3 | 125 | 90 | ||
| 2017 | 148 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 4 | 124 | 90 | ||
| 2017 | 149 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 5 | 120 | 90 | ||
| 2017 | 150 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 6 | 135 | 80 | ||
| 2017 | 151 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 7 | 150 | 90 | ||
| 2017 | 152 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 8 | 330 | 90 | ||
| 2017 | 153 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 9 | 201 | 80 | ||
| 2017 | 154 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 1 | 210 | 90 | ||
| 2017 | 155 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 2 | 100 | 90 | ||
| 2017 | 156 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 3 | 160 | 90 | ||
| 2017 | 157 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 4 | 260 | 90 | ||
| 2017 | 158 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 5 | ||||
| 2017 | 159 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 6 | 160 | 85 | ||
| 2017 | 160 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 7 | 210 | 80 | ||
| 2017 | 161 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 8 | 200 | 85 | ||
| 2017 | 162 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 9 | 225 | 90 | ||
| 2017 | 163 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 1 | 300 | 90 | ||
| 2017 | 164 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 2 | 195 | 70 | ||
| 2017 | 165 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 3 | 210 | 80 | ||
| 2017 | 166 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 4 | 230 | 80 | ||
| 2017 | 167 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 5 | 205 | 90 | ||
| 2017 | 168 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 6 | 204 | 80 | ||
| 2017 | 169 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 7 | 90 | 90 | ||
| 2017 | 170 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 8 | 180 | 70 | ||
| 2017 | 171 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 9 | 37 | 20 | ||
| 2017 | 172 | 231 | 2 | CHATO | JULIE | KENT | 3 | 1 | 305 | 90 | ||
| 2017 | 173 | 231 | 2 | CHATO | JULIE | KENT | 3 | 2 | 120 | 90 | ||
| 2017 | 174 | 231 | 2 | CHATO | JULIE | KENT | 3 | 3 | 160 | 80 | ||
| 2017 | 175 | 231 | 2 | CHATO | JULIE | KENT | 3 | 4 | 82 | 90 | ||
| 2017 | 176 | 231 | 2 | CHATO | JULIE | KENT | 3 | 5 | 110 | 90 | ||
| 2017 | 177 | 231 | 2 | CHATO | JULIE | KENT | 3 | 6 | 140 | 80 | ||
| 2017 | 178 | 231 | 2 | CHATO | JULIE | KENT | 3 | 7 | 208 | 85 | ||
| 2017 | 179 | 231 | 2 | CHATO | JULIE | KENT | 3 | 8 | 240 | 90 | ||
| 2017 | 180 | 231 | 2 | CHATO | JULIE | KENT | 3 | 9 | 160 | 90 | ||
| 2017 | 181 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 1 | 60 | 40 | ||
| 2017 | 182 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 2 | 113 | 50 | ||
| 2017 | 183 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 3 | 210 | 80 | ||
| 2017 | 184 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 4 | 260 | 90 | ||
| 2017 | 185 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 5 | 150 | 80 | ||
| 2017 | 186 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 6 | 80 | 50 | ||
| 2017 | 187 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 7 | 180 | 90 | ||
| 2017 | 188 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 8 | 196 | 80 | ||
| 2017 | 189 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 9 | 220 | 80 | ||
| 2017 | 190 | 221 | 7 | CHATO | CHATO | KENT | 3 | 1 | 230 | 90 | ||
| 2017 | 191 | 221 | 7 | CHATO | CHATO | KENT | 3 | 2 | 210 | 90 | ||
| 2017 | 192 | 221 | 7 | CHATO | CHATO | KENT | 3 | 3 | 150 | 85 | ||
| 2017 | 193 | 221 | 7 | CHATO | CHATO | KENT | 3 | 4 | 315 | 90 | ||
| 2017 | 194 | 221 | 7 | CHATO | CHATO | KENT | 3 | 5 | 220 | 90 | ||
| 2017 | 195 | 221 | 7 | CHATO | CHATO | KENT | 3 | 6 | ||||
| 2017 | 196 | 221 | 7 | CHATO | CHATO | KENT | 3 | 7 | 250 | 90 | ||
| 2017 | 197 | 221 | 7 | CHATO | CHATO | KENT | 3 | 8 | 160 | 80 | ||
| 2017 | 198 | 221 | 7 | CHATO | CHATO | KENT | 3 | 9 | 230 | 90 | ||
| 2017 | 199 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 1 | ||||
| 2017 | 200 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 2 | 280 | 90 | ||
| 2017 | 201 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 3 | 103 | 90 | ||
| 2017 | 202 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 4 | 180 | 90 | ||
| 2017 | 203 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 5 | 250 | 90 | ||
| 2017 | 204 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 6 | ||||
| 2017 | 205 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 7 | 190 | 90 | ||
| 2017 | 206 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 8 | 140 | 90 | ||
| 2017 | 207 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 9 | 210 | 80 | ||
| 2017 | 208 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 1 | 190 | 80 | ||
| 2017 | 209 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 2 | 220 | 90 | ||
| 2017 | 210 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 3 | 140 | 80 | ||
| 2017 | 211 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 4 | 210 | 75 | ||
| 2017 | 212 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 5 | 200 | 90 | ||
| 2017 | 213 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 6 | 290 | 90 | ||
| 2017 | 214 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 7 | 140 | 50 | ||
| 2017 | 215 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 8 | 170 | 90 | ||
| 2017 | 216 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 9 | 160 | 85 | ||
| 2018 | 1 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 1 | 95 | |||
| 2018 | 2 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 2 | 95 | |||
| 2018 | 3 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 3 | 315 | |||
| 2018 | 4 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 4 | ||||
| 2018 | 5 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 5 | 230 | |||
| 2018 | 6 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 6 | 232 | |||
| 2018 | 7 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 7 | 80 | |||
| 2018 | 8 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 8 | 90 | |||
| 2018 | 9 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 9 | 20 | |||
| 2018 | 10 | 231 | 2 | CHATO | JULIE | KENT | 1 | 1 | 80 | |||
| 2018 | 11 | 231 | 2 | CHATO | JULIE | KENT | 1 | 2 | 50 | |||
| 2018 | 12 | 231 | 2 | CHATO | JULIE | KENT | 1 | 3 | 92 | |||
| 2018 | 13 | 231 | 2 | CHATO | JULIE | KENT | 1 | 4 | 163 | |||
| 2018 | 14 | 231 | 2 | CHATO | JULIE | KENT | 1 | 5 | 5 | |||
| 2018 | 15 | 231 | 2 | CHATO | JULIE | KENT | 1 | 6 | 145 | |||
| 2018 | 16 | 231 | 2 | CHATO | JULIE | KENT | 1 | 7 | 80 | |||
| 2018 | 17 | 231 | 2 | CHATO | JULIE | KENT | 1 | 8 | 40 | |||
| 2018 | 18 | 231 | 2 | CHATO | JULIE | KENT | 1 | 9 | ||||
| 2018 | 19 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 1 | ||||
| 2018 | 20 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 2 | 90 | |||
| 2018 | 21 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 3 | 90 | |||
| 2018 | 22 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 4 | 295 | |||
| 2018 | 23 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 5 | 382 | |||
| 2018 | 24 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 6 | 270 | |||
| 2018 | 25 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 7 | 90 | |||
| 2018 | 26 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 8 | 90 | |||
| 2018 | 27 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 9 | 50 | |||
| 2018 | 28 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 1 | 50 | |||
| 2018 | 29 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 2 | 60 | |||
| 2018 | 30 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 3 | 242 | |||
| 2018 | 31 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 4 | 70 | |||
| 2018 | 32 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 5 | 320 | |||
| 2018 | 33 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 6 | 300 | |||
| 2018 | 34 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 7 | 80 | |||
| 2018 | 35 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 8 | 90 | |||
| 2018 | 36 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 9 | 95 | |||
| 2018 | 37 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 1 | 25 | |||
| 2018 | 38 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 2 | 250 | |||
| 2018 | 39 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 3 | 80 | |||
| 2018 | 40 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 4 | 240 | |||
| 2018 | 41 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 5 | 200 | |||
| 2018 | 42 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 6 | 10 | |||
| 2018 | 43 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 7 | 75 | |||
| 2018 | 44 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 8 | 60 | |||
| 2018 | 45 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 9 | 90 | |||
| 2018 | 46 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 1 | 20 | |||
| 2018 | 47 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 2 | 40 | |||
| 2018 | 48 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 3 | 70 | |||
| 2018 | 49 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 4 | 250 | |||
| 2018 | 50 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 5 | 195 | |||
| 2018 | 51 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 6 | 280 | |||
| 2018 | 52 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 7 | 30 | |||
| 2018 | 53 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 8 | 80 | |||
| 2018 | 54 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 9 | 90 | |||
| 2018 | 55 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 1 | 80 | |||
| 2018 | 56 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 2 | 146 | |||
| 2018 | 57 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 3 | 15 | |||
| 2018 | 58 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 4 | 138 | |||
| 2018 | 59 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 5 | 90 | |||
| 2018 | 60 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 6 | 190 | |||
| 2018 | 61 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 7 | ||||
| 2018 | 62 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 8 | 80 | |||
| 2018 | 63 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 9 | 95 | |||
| 2018 | 64 | 221 | 7 | CHATO | CHATO | KENT | 1 | 1 | 180 | |||
| 2018 | 65 | 221 | 7 | CHATO | CHATO | KENT | 1 | 2 | 50 | |||
| 2018 | 66 | 221 | 7 | CHATO | CHATO | KENT | 1 | 3 | 80 | |||
| 2018 | 67 | 221 | 7 | CHATO | CHATO | KENT | 1 | 4 | 80 | |||
| 2018 | 68 | 221 | 7 | CHATO | CHATO | KENT | 1 | 5 | 90 | |||
| 2018 | 69 | 221 | 7 | CHATO | CHATO | KENT | 1 | 6 | 178 | |||
| 2018 | 70 | 221 | 7 | CHATO | CHATO | KENT | 1 | 7 | ||||
| 2018 | 71 | 221 | 7 | CHATO | CHATO | KENT | 1 | 8 | 204 | |||
| 2018 | 72 | 221 | 7 | CHATO | CHATO | KENT | 1 | 9 | 97 | |||
| 2018 | 73 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 1 | ||||
| 2018 | 74 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 2 | 266 | 90 | ||
| 2018 | 75 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 3 | 187 | 85 | ||
| 2018 | 76 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 4 | 5 | |||
| 2018 | 77 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 5 | 220 | 90 | ||
| 2018 | 78 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 6 | 35 | |||
| 2018 | 79 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 7 | 90 | |||
| 2018 | 80 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 8 | 95 | |||
| 2018 | 81 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 9 | 90 | |||
| 2018 | 82 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 1 | 85 | |||
| 2018 | 83 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 2 | 108 | 90 | ||
| 2018 | 84 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 3 | 200 | 90 | ||
| 2018 | 85 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 4 | 95 | |||
| 2018 | 86 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 5 | 95 | |||
| 2018 | 87 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 6 | 90 | |||
| 2018 | 88 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 7 | 280 | 85 | ||
| 2018 | 89 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 8 | 90 | |||
| 2018 | 90 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 9 | 90 | |||
| 2018 | 91 | 231 | 2 | CHATO | JULIE | KENT | 2 | 1 | ||||
| 2018 | 92 | 231 | 2 | CHATO | JULIE | KENT | 2 | 2 | 300 | 85 | ||
| 2018 | 93 | 231 | 2 | CHATO | JULIE | KENT | 2 | 3 | 290 | 80 | ||
| 2018 | 94 | 231 | 2 | CHATO | JULIE | KENT | 2 | 4 | 50 | |||
| 2018 | 95 | 231 | 2 | CHATO | JULIE | KENT | 2 | 5 | 214 | 90 | ||
| 2018 | 96 | 231 | 2 | CHATO | JULIE | KENT | 2 | 6 | 90 | |||
| 2018 | 97 | 231 | 2 | CHATO | JULIE | KENT | 2 | 7 | 30 | |||
| 2018 | 98 | 231 | 2 | CHATO | JULIE | KENT | 2 | 8 | 85 | |||
| 2018 | 99 | 231 | 2 | CHATO | JULIE | KENT | 2 | 9 | 85 | |||
| 2018 | 100 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 1 | 305 | 85 | ||
| 2018 | 101 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 2 | 85 | |||
| 2018 | 102 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 3 | 75 | |||
| 2018 | 103 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 4 | 80 | |||
| 2018 | 104 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 5 | 230 | 75 | ||
| 2018 | 105 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 6 | 150 | 95 | ||
| 2018 | 106 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 7 | 80 | |||
| 2018 | 107 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 8 | 95 | |||
| 2018 | 108 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 9 | 80 | |||
| 2018 | 109 | 221 | 7 | CHATO | CHATO | KENT | 2 | 1 | 60 | |||
| 2018 | 110 | 221 | 7 | CHATO | CHATO | KENT | 2 | 2 | 80 | |||
| 2018 | 111 | 221 | 7 | CHATO | CHATO | KENT | 2 | 3 | 5 | |||
| 2018 | 112 | 221 | 7 | CHATO | CHATO | KENT | 2 | 4 | 3 | |||
| 2018 | 113 | 221 | 7 | CHATO | CHATO | KENT | 2 | 5 | 150 | 70 | ||
| 2018 | 114 | 221 | 7 | CHATO | CHATO | KENT | 2 | 6 | 140 | 30 | ||
| 2018 | 115 | 221 | 7 | CHATO | CHATO | KENT | 2 | 7 | 0 | |||
| 2018 | 116 | 221 | 7 | CHATO | CHATO | KENT | 2 | 8 | 150 | 10 | ||
| 2018 | 117 | 221 | 7 | CHATO | CHATO | KENT | 2 | 9 | 80 | |||
| 2018 | 118 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 1 | ||||
| 2018 | 119 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 2 | 95 | |||
| 2018 | 120 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 3 | 90 | |||
| 2018 | 121 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 4 | 85 | |||
| 2018 | 122 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 5 | 10 | |||
| 2018 | 123 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 6 | 5 | |||
| 2018 | 124 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 7 | 160 | 70 | ||
| 2018 | 125 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 8 | 325 | 90 | ||
| 2018 | 126 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 9 | 265 | 95 | ||
| 2018 | 127 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 1 | 80 | |||
| 2018 | 128 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 2 | 20 | |||
| 2018 | 129 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 3 | 65 | 20 | ||
| 2018 | 130 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 4 | 61 | 20 | ||
| 2018 | 131 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 5 | ||||
| 2018 | 132 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 6 | 255 | 95 | ||
| 2018 | 133 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 7 | 40 | |||
| 2018 | 134 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 8 | 60 | |||
| 2018 | 135 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 9 | 50 | |||
| 2018 | 136 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 1 | 20 | |||
| 2018 | 137 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 2 | 95 | |||
| 2018 | 138 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 3 | 124 | 90 | ||
| 2018 | 139 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 4 | 220 | 90 | ||
| 2018 | 140 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 5 | 260 | 95 | ||
| 2018 | 141 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 6 | ||||
| 2018 | 142 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 7 | 90 | |||
| 2018 | 143 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 8 | 95 | |||
| 2018 | 144 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 9 | 95 | |||
| 2018 | 145 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 1 | 95 | |||
| 2018 | 146 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 2 | 95 | |||
| 2018 | 147 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 3 | 95 | |||
| 2018 | 148 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 4 | 110 | 90 | ||
| 2018 | 149 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 5 | 147 | 95 | ||
| 2018 | 150 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 6 | 100 | |||
| 2018 | 151 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 7 | 75 | |||
| 2018 | 152 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 8 | 390 | 90 | ||
| 2018 | 153 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 9 | 95 | |||
| 2018 | 154 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 1 | 80 | |||
| 2018 | 155 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 2 | 95 | |||
| 2018 | 156 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 3 | 40 | |||
| 2018 | 157 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 4 | 160 | 65 | ||
| 2018 | 158 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 5 | ||||
| 2018 | 159 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 6 | 126 | 75 | ||
| 2018 | 160 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 7 | 20 | |||
| 2018 | 161 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 8 | 136 | 25 | ||
| 2018 | 162 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 9 | 40 | |||
| 2018 | 163 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 1 | 390 | 80 | ||
| 2018 | 164 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 2 | 95 | |||
| 2018 | 165 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 3 | 90 | |||
| 2018 | 166 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 4 | 70 | |||
| 2018 | 167 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 5 | 250 | 95 | ||
| 2018 | 168 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 6 | 95 | |||
| 2018 | 169 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 7 | 0 | |||
| 2018 | 170 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 8 | 272 | 90 | ||
| 2018 | 171 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 9 | 95 | |||
| 2018 | 172 | 231 | 2 | CHATO | JULIE | KENT | 3 | 1 | 203 | 50 | ||
| 2018 | 173 | 231 | 2 | CHATO | JULIE | KENT | 3 | 2 | 0 | |||
| 2018 | 174 | 231 | 2 | CHATO | JULIE | KENT | 3 | 3 | 0 | |||
| 2018 | 175 | 231 | 2 | CHATO | JULIE | KENT | 3 | 4 | 5 | |||
| 2018 | 176 | 231 | 2 | CHATO | JULIE | KENT | 3 | 5 | 2 | |||
| 2018 | 177 | 231 | 2 | CHATO | JULIE | KENT | 3 | 6 | 33 | 15 | ||
| 2018 | 178 | 231 | 2 | CHATO | JULIE | KENT | 3 | 7 | 116 | 40 | ||
| 2018 | 179 | 231 | 2 | CHATO | JULIE | KENT | 3 | 8 | 60 | |||
| 2018 | 180 | 231 | 2 | CHATO | JULIE | KENT | 3 | 9 | 50 | |||
| 2018 | 181 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 1 | 90 | |||
| 2018 | 182 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 2 | 95 | |||
| 2018 | 183 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 3 | 245 | 90 | ||
| 2018 | 184 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 4 | 290 | 90 | ||
| 2018 | 185 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 5 | 70 | |||
| 2018 | 186 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 6 | 85 | |||
| 2018 | 187 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 7 | 90 | |||
| 2018 | 188 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 8 | 80 | |||
| 2018 | 189 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 9 | 160 | 50 | ||
| 2018 | 190 | 221 | 7 | CHATO | CHATO | KENT | 3 | 1 | 220 | 80 | ||
| 2018 | 191 | 221 | 7 | CHATO | CHATO | KENT | 3 | 2 | 10 | |||
| 2018 | 192 | 221 | 7 | CHATO | CHATO | KENT | 3 | 3 | 0 | |||
| 2018 | 193 | 221 | 7 | CHATO | CHATO | KENT | 3 | 4 | 182 | 50 | ||
| 2018 | 194 | 221 | 7 | CHATO | CHATO | KENT | 3 | 5 | 0 | |||
| 2018 | 195 | 221 | 7 | CHATO | CHATO | KENT | 3 | 6 | ||||
| 2018 | 196 | 221 | 7 | CHATO | CHATO | KENT | 3 | 7 | 180 | 80 | ||
| 2018 | 197 | 221 | 7 | CHATO | CHATO | KENT | 3 | 8 | 5 | |||
| 2018 | 198 | 221 | 7 | CHATO | CHATO | KENT | 3 | 9 | 2 | |||
| 2018 | 199 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 1 | ||||
| 2018 | 200 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 2 | 85 | |||
| 2018 | 201 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 3 | 70 | |||
| 2018 | 202 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 4 | 213 | 70 | ||
| 2018 | 203 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 5 | 300 | 90 | ||
| 2018 | 204 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 6 | ||||
| 2018 | 205 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 7 | 10 | |||
| 2018 | 206 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 8 | 20 | |||
| 2018 | 207 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 9 | 200 | 60 | ||
| 2018 | 208 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 1 | 80 | |||
| 2018 | 209 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 2 | 25 | |||
| 2018 | 210 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 3 | 60 | |||
| 2018 | 211 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 4 | 210 | 60 | ||
| 2018 | 212 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 5 | 75 | 15 | ||
| 2018 | 213 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 6 | 188 | 40 | ||
| 2018 | 214 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 7 | 10 | |||
| 2018 | 215 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 8 | 80 | |||
| 2018 | 216 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 9 | 40 | |||
| 2019 | 1 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 1 | 3.15 | 180 | 95 | 80 |
| 2019 | 2 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 2 | 3.60 | 280 | 90 | 75 |
| 2019 | 3 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 3 | 3.65 | 234 | 80 | 70 |
| 2019 | 4 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 4 | ||||
| 2019 | 5 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 5 | 3.00 | 110 | 90 | 40 |
| 2019 | 6 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 6 | 3.40 | 202 | 95 | 80 |
| 2019 | 7 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 7 | 3.40 | 202 | 80 | 75 |
| 2019 | 8 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 8 | 3.20 | 108 | 70 | 50 |
| 2019 | 9 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 9 | 2.70 | 80 | 90 | 0 |
| 2019 | 10 | 231 | 2 | CHATO | JULIE | KENT | 1 | 1 | 3.65 | 245 | 85 | 5 |
| 2019 | 11 | 231 | 2 | CHATO | JULIE | KENT | 1 | 2 | 3.95 | 228 | 80 | 25 |
| 2019 | 12 | 231 | 2 | CHATO | JULIE | KENT | 1 | 3 | 4.85 | 320 | 95 | 20 |
| 2019 | 13 | 231 | 2 | CHATO | JULIE | KENT | 1 | 4 | 4.35 | 307 | 90 | 40 |
| 2019 | 14 | 231 | 2 | CHATO | JULIE | KENT | 1 | 5 | 4.00 | 251 | 80 | 75 |
| 2019 | 15 | 231 | 2 | CHATO | JULIE | KENT | 1 | 6 | 4.20 | 264 | 70 | 35 |
| 2019 | 16 | 231 | 2 | CHATO | JULIE | KENT | 1 | 7 | 4.25 | 280 | 95 | 65 |
| 2019 | 17 | 231 | 2 | CHATO | JULIE | KENT | 1 | 8 | 4.80 | 288 | 95 | 80 |
| 2019 | 18 | 231 | 2 | CHATO | JULIE | KENT | 1 | 9 | 70 | |||
| 2019 | 19 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 1 | 4.05 | 70 | ||
| 2019 | 20 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 2 | 4.00 | 122 | 90 | 80 |
| 2019 | 21 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 3 | 3.70 | 118 | 90 | 80 |
| 2019 | 22 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 4 | 4.25 | 152 | 90 | 75 |
| 2019 | 23 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 5 | 4.35 | 333 | 90 | 40 |
| 2019 | 24 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 6 | 3.70 | 221 | 95 | 75 |
| 2019 | 25 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 7 | 4.50 | 304 | 85 | 90 |
| 2019 | 26 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 8 | 4.15 | 182 | 80 | 90 |
| 2019 | 27 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 9 | 3.95 | 210 | 95 | 70 |
| 2019 | 28 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 1 | 4.20 | 395 | 90 | 30 |
| 2019 | 29 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 2 | 3.95 | 160 | 90 | 75 |
| 2019 | 30 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 3 | 4.15 | 226 | 90 | 70 |
| 2019 | 31 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 4 | 4.45 | 194 | 85 | 70 |
| 2019 | 32 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 5 | 4.10 | 315 | 75 | 60 |
| 2019 | 33 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 6 | 4.45 | 130 | 65 | 30 |
| 2019 | 34 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 7 | 4.40 | 175 | 80 | 30 |
| 2019 | 35 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 8 | 4.00 | 140 | 80 | 60 |
| 2019 | 36 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 9 | 3.80 | 97 | 65 | 60 |
| 2019 | 37 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 1 | 3.00 | 125 | 90 | 80 |
| 2019 | 38 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 2 | 3.95 | 185 | 70 | 65 |
| 2019 | 39 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 3 | 4.10 | 203 | 80 | 90 |
| 2019 | 40 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 4 | 3.65 | 160 | 90 | 45 |
| 2019 | 41 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 5 | 3.65 | 137 | 90 | 60 |
| 2019 | 42 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 6 | 3.10 | 138 | 95 | 65 |
| 2019 | 43 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 7 | 3.70 | 184 | 95 | 80 |
| 2019 | 44 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 8 | 3.60 | 144 | 90 | 80 |
| 2019 | 45 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 9 | 3.80 | 210 | 85 | 75 |
| 2019 | 46 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 1 | 4.45 | 219 | 90 | 80 |
| 2019 | 47 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 2 | 4.65 | 240 | 90 | 70 |
| 2019 | 48 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 3 | 4.25 | 265 | 95 | 85 |
| 2019 | 49 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 4 | 4.35 | 215 | 95 | 75 |
| 2019 | 50 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 5 | 4.45 | 361 | 90 | 75 |
| 2019 | 51 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 6 | 4.05 | 144 | 80 | 75 |
| 2019 | 52 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 7 | 4.35 | 215 | 85 | 70 |
| 2019 | 53 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 8 | 4.10 | 104 | 90 | 45 |
| 2019 | 54 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 9 | 4.05 | 97 | 70 | 75 |
| 2019 | 55 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 1 | 4.30 | 76 | 60 | 40 |
| 2019 | 56 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 2 | 3.65 | 220 | 90 | 65 |
| 2019 | 57 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 3 | 4.10 | 245 | 80 | 60 |
| 2019 | 58 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 4 | 3.70 | 220 | 95 | 70 |
| 2019 | 59 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 5 | 3.40 | 98 | 80 | 30 |
| 2019 | 60 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 6 | 3.85 | 172 | 95 | 80 |
| 2019 | 61 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 7 | ||||
| 2019 | 62 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 8 | 3.45 | 148 | 80 | 80 |
| 2019 | 63 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 9 | ||||
| 2019 | 64 | 221 | 7 | CHATO | CHATO | KENT | 1 | 1 | 4.45 | 206 | 95 | 20 |
| 2019 | 65 | 221 | 7 | CHATO | CHATO | KENT | 1 | 2 | 3.65 | 260 | 95 | 50 |
| 2019 | 66 | 221 | 7 | CHATO | CHATO | KENT | 1 | 3 | 3.40 | 132 | 95 | 70 |
| 2019 | 67 | 221 | 7 | CHATO | CHATO | KENT | 1 | 4 | 3.15 | 25 | 70 | |
| 2019 | 68 | 221 | 7 | CHATO | CHATO | KENT | 1 | 5 | 3.35 | 51 | 80 | 70 |
| 2019 | 69 | 221 | 7 | CHATO | CHATO | KENT | 1 | 6 | 4.25 | 210 | 95 | 70 |
| 2019 | 70 | 221 | 7 | CHATO | CHATO | KENT | 1 | 7 | 3.30 | 65 | 80 | 80 |
| 2019 | 71 | 221 | 7 | CHATO | CHATO | KENT | 1 | 8 | 3.85 | 217 | 80 | 70 |
| 2019 | 72 | 221 | 7 | CHATO | CHATO | KENT | 1 | 9 | 3.00 | 65 | 85 | 70 |
| 2019 | 73 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 1 | 4.85 | 23 | 30 | 20 |
| 2019 | 74 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 2 | 4.05 | 164 | 90 | 70 |
| 2019 | 75 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 3 | 3.95 | 187 | 70 | 70 |
| 2019 | 76 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 4 | 3.10 | 34 | 70 | 40 |
| 2019 | 77 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 5 | 3.05 | 167 | 80 | 65 |
| 2019 | 78 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 6 | 3.40 | 130 | 90 | 45 |
| 2019 | 79 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 7 | 4.05 | 312 | 60 | 60 |
| 2019 | 80 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 8 | 3.75 | 136 | 60 | 40 |
| 2019 | 81 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 9 | 3.70 | 139 | 85 | 65 |
| 2019 | 82 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 1 | 3.45 | 185 | 85 | 70 |
| 2019 | 83 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 2 | 3.75 | 58 | 90 | 50 |
| 2019 | 84 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 3 | 3.70 | 118 | 90 | 65 |
| 2019 | 85 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 4 | 3.75 | 152 | 70 | 60 |
| 2019 | 86 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 5 | 3.65 | 75 | 90 | |
| 2019 | 87 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 6 | 4.05 | 187 | 90 | 70 |
| 2019 | 88 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 7 | 3.95 | 120 | 80 | 80 |
| 2019 | 89 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 8 | 3.40 | 150 | 90 | 40 |
| 2019 | 90 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 9 | 2.90 | 87 | 70 | 70 |
| 2019 | 91 | 231 | 2 | CHATO | JULIE | KENT | 2 | 1 | 2.00 | |||
| 2019 | 92 | 231 | 2 | CHATO | JULIE | KENT | 2 | 2 | 3.90 | 142 | 95 | 70 |
| 2019 | 93 | 231 | 2 | CHATO | JULIE | KENT | 2 | 3 | 3.90 | 260 | 90 | 75 |
| 2019 | 94 | 231 | 2 | CHATO | JULIE | KENT | 2 | 4 | 3.10 | 124 | 90 | 20 |
| 2019 | 95 | 231 | 2 | CHATO | JULIE | KENT | 2 | 5 | 3.60 | 132 | 80 | 70 |
| 2019 | 96 | 231 | 2 | CHATO | JULIE | KENT | 2 | 6 | 3.85 | 103 | 60 | 65 |
| 2019 | 97 | 231 | 2 | CHATO | JULIE | KENT | 2 | 7 | 3.65 | 104 | 85 | 65 |
| 2019 | 98 | 231 | 2 | CHATO | JULIE | KENT | 2 | 8 | 3.70 | 123 | 60 | 80 |
| 2019 | 99 | 231 | 2 | CHATO | JULIE | KENT | 2 | 9 | 3.35 | 139 | 70 | 90 |
| 2019 | 100 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 1 | 3.85 | 260 | 90 | 75 |
| 2019 | 101 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 2 | 3.55 | 215 | 90 | 35 |
| 2019 | 102 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 3 | 3.80 | 103 | 90 | 75 |
| 2019 | 103 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 4 | 3.45 | 181 | 90 | 65 |
| 2019 | 104 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 5 | 4.15 | 360 | 80 | 80 |
| 2019 | 105 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 6 | 3.45 | 98 | 60 | 20 |
| 2019 | 106 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 7 | 3.40 | 229 | 95 | 70 |
| 2019 | 107 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 8 | 3.30 | 159 | 90 | 70 |
| 2019 | 108 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 9 | 3.40 | 211 | 90 | 60 |
| 2019 | 109 | 221 | 7 | CHATO | CHATO | KENT | 2 | 1 | 3.35 | 88 | 70 | 40 |
| 2019 | 110 | 221 | 7 | CHATO | CHATO | KENT | 2 | 2 | 3.15 | 164 | 80 | 50 |
| 2019 | 111 | 221 | 7 | CHATO | CHATO | KENT | 2 | 3 | 3.30 | 127 | 70 | 50 |
| 2019 | 112 | 221 | 7 | CHATO | CHATO | KENT | 2 | 4 | 4.25 | 130 | 90 | 30 |
| 2019 | 113 | 221 | 7 | CHATO | CHATO | KENT | 2 | 5 | 2.80 | 218 | 70 | 65 |
| 2019 | 114 | 221 | 7 | CHATO | CHATO | KENT | 2 | 6 | 4.35 | 280 | 90 | 50 |
| 2019 | 115 | 221 | 7 | CHATO | CHATO | KENT | 2 | 7 | 3.95 | 125 | 80 | 50 |
| 2019 | 116 | 221 | 7 | CHATO | CHATO | KENT | 2 | 8 | 4.35 | 150 | 80 | 40 |
| 2019 | 117 | 221 | 7 | CHATO | CHATO | KENT | 2 | 9 | 3.50 | 102 | 80 | 50 |
| 2019 | 118 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 1 | ||||
| 2019 | 119 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 2 | 3.30 | |||
| 2019 | 120 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 3 | 3.20 | 95 | 90 | 60 |
| 2019 | 121 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 4 | 3.60 | 134 | 70 | 60 |
| 2019 | 122 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 5 | 3.70 | 205 | 70 | 30 |
| 2019 | 123 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 6 | 4.10 | 152 | 90 | 30 |
| 2019 | 124 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 7 | 3.90 | 125 | 90 | 60 |
| 2019 | 125 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 8 | 4.20 | 219 | 70 | 80 |
| 2019 | 126 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 9 | 3.50 | 241 | 80 | 80 |
| 2019 | 127 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 1 | 3.30 | 172 | 60 | |
| 2019 | 128 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 2 | 3.50 | 220 | 85 | 75 |
| 2019 | 129 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 3 | 3.85 | 152 | 90 | 70 |
| 2019 | 130 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 4 | 3.95 | 130 | 90 | 50 |
| 2019 | 131 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 5 | 1.90 | 3 | 60 | 90 |
| 2019 | 132 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 6 | 1.85 | 216 | 80 | 70 |
| 2019 | 133 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 7 | 4.30 | 181 | 90 | 90 |
| 2019 | 134 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 8 | 3.45 | 176 | 80 | 70 |
| 2019 | 135 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 9 | 2.75 | 75 | 90 | 10 |
| 2019 | 136 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 1 | 2.75 | 120 | 90 | 70 |
| 2019 | 137 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 2 | 3.50 | 151 | 50 | 70 |
| 2019 | 138 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 3 | 3.40 | 135 | 80 | 80 |
| 2019 | 139 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 4 | 3.65 | 250 | 70 | 80 |
| 2019 | 140 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 5 | 3.10 | 188 | 70 | 75 |
| 2019 | 141 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 6 | ||||
| 2019 | 142 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 7 | 2.90 | 121 | 90 | 40 |
| 2019 | 143 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 8 | 3.45 | 138 | 70 | 80 |
| 2019 | 144 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 9 | 2.90 | 145 | 90 | 70 |
| 2019 | 145 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 1 | 3.20 | 271 | 50 | 50 |
| 2019 | 146 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 2 | 3.40 | 221 | 40 | 60 |
| 2019 | 147 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 3 | 3.60 | 208 | 80 | 70 |
| 2019 | 148 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 4 | 3.30 | 168 | 50 | 45 |
| 2019 | 149 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 5 | 3.00 | 42 | 7 | 15 |
| 2019 | 150 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 6 | 2.85 | 150 | 50 | 65 |
| 2019 | 151 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 7 | 3.65 | 214 | 70 | 75 |
| 2019 | 152 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 8 | 3.65 | 346 | 70 | 80 |
| 2019 | 153 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 9 | 3.00 | 190 | 50 | 60 |
| 2019 | 154 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 1 | 4.20 | 400 | 90 | 80 |
| 2019 | 155 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 2 | 3.30 | 183 | 60 | |
| 2019 | 156 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 3 | 4.30 | 263 | 90 | 10 |
| 2019 | 157 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 4 | 3.30 | 250 | 55 | 70 |
| 2019 | 158 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 5 | ||||
| 2019 | 159 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 6 | 3.65 | 262 | 90 | 65 |
| 2019 | 160 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 7 | 3.65 | 382 | 90 | 30 |
| 2019 | 161 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 8 | 4.00 | 475 | 90 | 30 |
| 2019 | 162 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 9 | 4.05 | 393 | 90 | 60 |
| 2019 | 163 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 1 | 4.15 | 470 | 90 | 70 |
| 2019 | 164 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 2 | 4.20 | 287 | 80 | 80 |
| 2019 | 165 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 3 | 4.15 | 414 | 80 | 80 |
| 2019 | 166 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 4 | 3.16 | 497 | 75 | 80 |
| 2019 | 167 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 5 | 3.85 | 279 | 90 | 75 |
| 2019 | 168 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 6 | 3.40 | 179 | 50 | 75 |
| 2019 | 169 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 7 | 3.40 | 208 | 95 | 20 |
| 2019 | 170 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 8 | 3.20 | 256 | 90 | 70 |
| 2019 | 171 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 9 | 2.80 | 104 | 80 | 75 |
| 2019 | 172 | 231 | 2 | CHATO | JULIE | KENT | 3 | 1 | 4.45 | 539 | 90 | 30 |
| 2019 | 173 | 231 | 2 | CHATO | JULIE | KENT | 3 | 2 | 3.70 | 402 | 90 | 20 |
| 2019 | 174 | 231 | 2 | CHATO | JULIE | KENT | 3 | 3 | 3.85 | 310 | 90 | 20 |
| 2019 | 175 | 231 | 2 | CHATO | JULIE | KENT | 3 | 4 | 3.30 | 103 | 90 | 50 |
| 2019 | 176 | 231 | 2 | CHATO | JULIE | KENT | 3 | 5 | 3.40 | 50 | 60 | 50 |
| 2019 | 177 | 231 | 2 | CHATO | JULIE | KENT | 3 | 6 | 3.40 | 200 | 80 | 10 |
| 2019 | 178 | 231 | 2 | CHATO | JULIE | KENT | 3 | 7 | 3.95 | 324 | 90 | 75 |
| 2019 | 179 | 231 | 2 | CHATO | JULIE | KENT | 3 | 8 | 4.05 | 354 | 90 | 75 |
| 2019 | 180 | 231 | 2 | CHATO | JULIE | KENT | 3 | 9 | 3.25 | 135 | 70 | 70 |
| 2019 | 181 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 1 | 2.80 | 130 | 80 | 70 |
| 2019 | 182 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 2 | 3.00 | 140 | 80 | 40 |
| 2019 | 183 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 3 | 3.65 | 284 | 80 | 80 |
| 2019 | 184 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 4 | 3.65 | 261 | 90 | 80 |
| 2019 | 185 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 5 | 3.75 | 220 | 95 | 20 |
| 2019 | 186 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 6 | 3.15 | 175 | 70 | 80 |
| 2019 | 187 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 7 | 3.60 | 310 | 95 | 70 |
| 2019 | 188 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 8 | 3.60 | 440 | 90 | 70 |
| 2019 | 189 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 9 | 4.20 | 415 | 90 | 70 |
| 2019 | 190 | 221 | 7 | CHATO | CHATO | KENT | 3 | 1 | 3.70 | 360 | 50 | 70 |
| 2019 | 191 | 221 | 7 | CHATO | CHATO | KENT | 3 | 2 | 4.70 | 230 | 90 | 15 |
| 2019 | 192 | 221 | 7 | CHATO | CHATO | KENT | 3 | 3 | 4.10 | 350 | 90 | 20 |
| 2019 | 193 | 221 | 7 | CHATO | CHATO | KENT | 3 | 4 | 4.00 | 423 | 90 | 70 |
| 2019 | 194 | 221 | 7 | CHATO | CHATO | KENT | 3 | 5 | 3.50 | 304 | 90 | 60 |
| 2019 | 195 | 221 | 7 | CHATO | CHATO | KENT | 3 | 6 | ||||
| 2019 | 196 | 221 | 7 | CHATO | CHATO | KENT | 3 | 7 | 4.00 | 410 | 90 | 80 |
| 2019 | 197 | 221 | 7 | CHATO | CHATO | KENT | 3 | 8 | 3.90 | 380 | 90 | 80 |
| 2019 | 198 | 221 | 7 | CHATO | CHATO | KENT | 3 | 9 | 4.05 | 340 | 90 | 50 |
| 2019 | 199 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 1 | ||||
| 2019 | 200 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 2 | 3.70 | 268 | 80 | 80 |
| 2019 | 201 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 3 | 3.40 | 190 | 85 | 80 |
| 2019 | 202 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 4 | 3.75 | 214 | 80 | 80 |
| 2019 | 203 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 5 | 3.70 | 380 | 90 | 80 |
| 2019 | 204 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 6 | 214 | |||
| 2019 | 205 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 7 | 3.60 | 300 | 95 | 80 |
| 2019 | 206 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 8 | 3.40 | 325 | 90 | 60 |
| 2019 | 207 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 9 | 3.70 | 350 | 90 | 70 |
| 2019 | 208 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 1 | 3.50 | 180 | 80 | 75 |
| 2019 | 209 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 2 | 4.40 | 295 | 90 | 25 |
| 2019 | 210 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 3 | 3.60 | 232 | 70 | 50 |
| 2019 | 211 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 4 | 4.05 | 250 | 70 | 80 |
| 2019 | 212 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 5 | 4.10 | 340 | 90 | 80 |
| 2019 | 213 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 6 | 4.05 | 382 | 80 | 80 |
| 2019 | 214 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 7 | 3.70 | 379 | 90 | 70 |
| 2019 | 215 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 8 | 3.50 | 120 | 80 | 70 |
| 2019 | 216 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 9 | 3.65 | 260 | 90 | 70 |
fru %>% kable(caption = "Evaluation of mango fruit quality", align = 'c')| year | n | treat | n_treat | stock | edge | scion | block | n_plant | sample | n_fruits | weigth | long | diameter_1 | diameter_2 | diameter_average |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2023 | 1 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 1 | 1 | 26 | 270 | 86 | 78 | 74 | 76.0 |
| 2023 | 2 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 1 | 2 | 26 | 520 | 111 | 90 | 83 | 86.5 |
| 2023 | 3 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 1 | 3 | 26 | 385 | 103 | 86 | 75 | 80.5 |
| 2023 | 4 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 1 | 4 | 26 | 230 | 86 | 70 | 69 | 69.5 |
| 2023 | 5 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 1 | 5 | 26 | 285 | 88 | 78 | 71 | 74.5 |
| 2023 | 6 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 2 | 1 | 35 | 600 | 116 | 96 | 87 | 91.5 |
| 2023 | 7 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 2 | 2 | 35 | 457 | 101 | 88 | 88 | 88.0 |
| 2023 | 8 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 2 | 3 | 35 | 520 | 115 | 88 | 81 | 84.5 |
| 2023 | 9 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 2 | 4 | 35 | 665 | 126 | 103 | 95 | 99.0 |
| 2023 | 10 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 1 | 2 | 5 | 35 | 305 | 91 | 78 | 80 | 79.0 |
| 2023 | 11 | 231 | 2 | CHATO | JULIE | KENT | 1 | 1 | 1 | 118 | 422 | 100 | 91 | 83 | 87.0 |
| 2023 | 12 | 231 | 2 | CHATO | JULIE | KENT | 1 | 1 | 2 | 118 | 377 | 102 | 84 | 76 | 80.0 |
| 2023 | 13 | 231 | 2 | CHATO | JULIE | KENT | 1 | 1 | 3 | 118 | 300 | 91 | 84 | 72 | 78.0 |
| 2023 | 14 | 231 | 2 | CHATO | JULIE | KENT | 1 | 1 | 4 | 118 | 455 | 106 | 88 | 82 | 85.0 |
| 2023 | 15 | 231 | 2 | CHATO | JULIE | KENT | 1 | 1 | 5 | 118 | 485 | 108 | 91 | 83 | 87.0 |
| 2023 | 16 | 231 | 2 | CHATO | JULIE | KENT | 1 | 2 | 1 | 102 | 420 | 104 | 87 | 83 | 85.0 |
| 2023 | 17 | 231 | 2 | CHATO | JULIE | KENT | 1 | 2 | 2 | 102 | 395 | 99 | 86 | 80 | 83.0 |
| 2023 | 18 | 231 | 2 | CHATO | JULIE | KENT | 1 | 2 | 3 | 102 | 335 | 98 | 87 | 70 | 78.5 |
| 2023 | 19 | 231 | 2 | CHATO | JULIE | KENT | 1 | 2 | 4 | 102 | 610 | 118 | 99 | 92 | 95.5 |
| 2023 | 20 | 231 | 2 | CHATO | JULIE | KENT | 1 | 2 | 5 | 102 | 530 | 109 | 98 | 90 | 94.0 |
| 2023 | 21 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 1 | 1 | 86 | 485 | 105 | 90 | 83 | 86.5 |
| 2023 | 22 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 1 | 2 | 86 | 460 | 103 | 89 | 80 | 84.5 |
| 2023 | 23 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 1 | 3 | 86 | 576 | 111 | 101 | 86 | 93.5 |
| 2023 | 24 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 1 | 4 | 86 | 610 | 114 | 97 | 91 | 94.0 |
| 2023 | 25 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 1 | 5 | 86 | 505 | 111 | 92 | 85 | 88.5 |
| 2023 | 26 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 2 | 1 | 105 | 475 | 109 | 88 | 84 | 86.0 |
| 2023 | 27 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 2 | 2 | 105 | 350 | 95 | 83 | 77 | 80.0 |
| 2023 | 28 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 2 | 3 | 105 | 345 | 96 | 86 | 74 | 80.0 |
| 2023 | 29 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 2 | 4 | 105 | 475 | 101 | 95 | 86 | 90.5 |
| 2023 | 30 | 241 | 3 | CHULUCANAS | CHATO | KENT | 1 | 2 | 5 | 105 | 490 | 111 | 97 | 83 | 90.0 |
| 2023 | 31 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 1 | 1 | 16 | 560 | 104 | 99 | 90 | 94.5 |
| 2023 | 32 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 1 | 2 | 16 | 381 | 96 | 83 | 82 | 82.5 |
| 2023 | 33 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 1 | 3 | 16 | 556 | 108 | 95 | 89 | 92.0 |
| 2023 | 34 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 1 | 4 | 16 | 432 | 100 | 89 | 82 | 85.5 |
| 2023 | 35 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 1 | 5 | 16 | 475 | 103 | 89 | 81 | 85.0 |
| 2023 | 36 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 2 | 1 | 97 | 600 | 112 | 99 | 89 | 94.0 |
| 2023 | 37 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 2 | 2 | 97 | 485 | 108 | 93 | 85 | 89.0 |
| 2023 | 38 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 2 | 3 | 97 | 500 | 108 | 91 | 88 | 89.5 |
| 2023 | 39 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 2 | 4 | 97 | 550 | 111 | 96 | 86 | 91.0 |
| 2023 | 40 | 211 | 4 | CHATO | IRWIN | KENT | 1 | 2 | 5 | 97 | 695 | 119 | 106 | 94 | 100.0 |
| 2023 | 41 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 1 | 1 | 94 | 367 | 100 | 82 | 80 | 81.0 |
| 2023 | 42 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 1 | 2 | 94 | 448 | 110 | 89 | 78 | 83.5 |
| 2023 | 43 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 1 | 3 | 94 | 400 | 104 | 87 | 77 | 82.0 |
| 2023 | 44 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 1 | 4 | 94 | 409 | 106 | 86 | 78 | 82.0 |
| 2023 | 45 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 1 | 5 | 94 | 402 | 102 | 90 | 80 | 85.0 |
| 2023 | 46 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 2 | 1 | 118 | 460 | 107 | 86 | 80 | 83.0 |
| 2023 | 47 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 2 | 2 | 118 | 450 | 107 | 94 | 81 | 87.5 |
| 2023 | 48 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 2 | 3 | 118 | 416 | 108 | 82 | 77 | 79.5 |
| 2023 | 49 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 2 | 4 | 118 | 500 | 107 | 97 | 85 | 91.0 |
| 2023 | 50 | 131 | 5 | CHULUCANAS | JULIE | KENT | 1 | 2 | 5 | 118 | 465 | 112 | 93 | 82 | 87.5 |
| 2023 | 51 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 1 | 1 | 91 | 605 | 120 | 94 | 91 | 92.5 |
| 2023 | 52 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 1 | 2 | 91 | 585 | 122 | 93 | 86 | 89.5 |
| 2023 | 53 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 1 | 3 | 91 | 415 | 106 | 85 | 79 | 82.0 |
| 2023 | 54 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 1 | 4 | 91 | 460 | 103 | 89 | 81 | 85.0 |
| 2023 | 55 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 1 | 5 | 91 | 455 | 105 | 86 | 82 | 84.0 |
| 2023 | 56 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 2 | 1 | 71 | 375 | 96 | 88 | 79 | 83.5 |
| 2023 | 57 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 2 | 2 | 71 | 455 | 108 | 94 | 84 | 89.0 |
| 2023 | 58 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 2 | 3 | 71 | 410 | 101 | 84 | 77 | 80.5 |
| 2023 | 59 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 2 | 4 | 71 | 460 | 110 | 89 | 79 | 84.0 |
| 2023 | 60 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 1 | 2 | 5 | 71 | 385 | 105 | 82 | 78 | 80.0 |
| 2023 | 61 | 221 | 7 | CHATO | CHATO | KENT | 1 | 1 | 1 | 13 | 440 | 100 | 90 | 81 | 85.5 |
| 2023 | 62 | 221 | 7 | CHATO | CHATO | KENT | 1 | 1 | 2 | 13 | 450 | 104 | 90 | 84 | 87.0 |
| 2023 | 63 | 221 | 7 | CHATO | CHATO | KENT | 1 | 1 | 3 | 13 | 540 | 110 | 91 | 88 | 89.5 |
| 2023 | 64 | 221 | 7 | CHATO | CHATO | KENT | 1 | 1 | 4 | 13 | 368 | 97 | 82 | 81 | 81.5 |
| 2023 | 65 | 221 | 7 | CHATO | CHATO | KENT | 1 | 1 | 5 | 13 | 341 | 93 | 85 | 78 | 81.5 |
| 2023 | 66 | 221 | 7 | CHATO | CHATO | KENT | 1 | 2 | 1 | 31 | 500 | 117 | 92 | 79 | 85.5 |
| 2023 | 67 | 221 | 7 | CHATO | CHATO | KENT | 1 | 2 | 2 | 31 | 305 | 96 | 81 | 71 | 76.0 |
| 2023 | 68 | 221 | 7 | CHATO | CHATO | KENT | 1 | 2 | 3 | 31 | 425 | 103 | 89 | 82 | 85.5 |
| 2023 | 69 | 221 | 7 | CHATO | CHATO | KENT | 1 | 2 | 4 | 31 | 360 | 101 | 82 | 78 | 80.0 |
| 2023 | 70 | 221 | 7 | CHATO | CHATO | KENT | 1 | 2 | 5 | 31 | 380 | 101 | 84 | 78 | 81.0 |
| 2023 | 71 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 1 | 1 | 29 | 340 | 95 | 80 | 77 | 78.5 |
| 2023 | 72 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 1 | 2 | 29 | 390 | 100 | 82 | 77 | 79.5 |
| 2023 | 73 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 1 | 3 | 29 | 480 | 110 | 92 | 81 | 86.5 |
| 2023 | 74 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 1 | 4 | 29 | 440 | 102 | 87 | 80 | 83.5 |
| 2023 | 75 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 1 | 5 | 29 | 450 | 104 | 90 | 83 | 86.5 |
| 2023 | 76 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 2 | 1 | 62 | 371 | 100 | 83 | 78 | 80.5 |
| 2023 | 77 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 2 | 2 | 62 | 381 | 95 | 89 | 81 | 85.0 |
| 2023 | 78 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 2 | 3 | 62 | 380 | 102 | 87 | 79 | 83.0 |
| 2023 | 79 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 2 | 4 | 62 | 452 | 105 | 91 | 84 | 87.5 |
| 2023 | 80 | 121 | 8 | CHATO | CHULUCANAS | KENT | 1 | 2 | 5 | 62 | 455 | 104 | 90 | 84 | 87.0 |
| 2023 | 81 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 1 | 1 | 51 | 385 | 98 | 90 | 79 | 84.5 |
| 2023 | 82 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 1 | 2 | 51 | 610 | 119 | 96 | 87 | 91.5 |
| 2023 | 83 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 1 | 3 | 51 | 640 | 120 | 100 | 86 | 93.0 |
| 2023 | 84 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 1 | 4 | 51 | 430 | 103 | 92 | 80 | 86.0 |
| 2023 | 85 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 1 | 5 | 51 | 500 | 107 | 95 | 87 | 91.0 |
| 2023 | 86 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 2 | 1 | 38 | 630 | 118 | 101 | 91 | 96.0 |
| 2023 | 87 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 2 | 2 | 38 | 512 | 107 | 97 | 86 | 91.5 |
| 2023 | 88 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 2 | 3 | 38 | 652 | 126 | 102 | 83 | 92.5 |
| 2023 | 89 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 2 | 4 | 38 | 510 | 108 | 93 | 88 | 90.5 |
| 2023 | 90 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 2 | 2 | 5 | 38 | 495 | 110 | 95 | 84 | 89.5 |
| 2023 | 91 | 231 | 2 | CHATO | JULIE | KENT | 2 | 1 | 1 | 57 | 441 | 102 | 93 | 82 | 87.5 |
| 2023 | 92 | 231 | 2 | CHATO | JULIE | KENT | 2 | 1 | 2 | 57 | 471 | 105 | 88 | 83 | 85.5 |
| 2023 | 93 | 231 | 2 | CHATO | JULIE | KENT | 2 | 1 | 3 | 57 | 645 | 120 | 100 | 95 | 97.5 |
| 2023 | 94 | 231 | 2 | CHATO | JULIE | KENT | 2 | 1 | 4 | 57 | 525 | 114 | 90 | 85 | 87.5 |
| 2023 | 95 | 231 | 2 | CHATO | JULIE | KENT | 2 | 1 | 5 | 57 | 360 | 101 | 89 | 72 | 80.5 |
| 2023 | 96 | 231 | 2 | CHATO | JULIE | KENT | 2 | 2 | 1 | 116 | 555 | 115 | 99 | 87 | 93.0 |
| 2023 | 97 | 231 | 2 | CHATO | JULIE | KENT | 2 | 2 | 2 | 116 | 495 | 116 | 91 | 80 | 85.5 |
| 2023 | 98 | 231 | 2 | CHATO | JULIE | KENT | 2 | 2 | 3 | 116 | 512 | 114 | 93 | 84 | 88.5 |
| 2023 | 99 | 231 | 2 | CHATO | JULIE | KENT | 2 | 2 | 4 | 116 | 605 | 119 | 95 | 85 | 90.0 |
| 2023 | 100 | 231 | 2 | CHATO | JULIE | KENT | 2 | 2 | 5 | 116 | 520 | 109 | 99 | 87 | 93.0 |
| 2023 | 101 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 1 | 1 | 91 | 425 | 102 | 91 | 82 | 86.5 |
| 2023 | 102 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 1 | 2 | 91 | 600 | 118 | 101 | 88 | 94.5 |
| 2023 | 103 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 1 | 3 | 91 | 765 | 119 | 107 | 94 | 100.5 |
| 2023 | 104 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 1 | 4 | 91 | 426 | 108 | 87 | 76 | 81.5 |
| 2023 | 105 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 1 | 5 | 91 | 475 | 106 | 97 | 84 | 90.5 |
| 2023 | 106 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 2 | 1 | 94 | 545 | 109 | 95 | 86 | 90.5 |
| 2023 | 107 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 2 | 2 | 94 | 371 | 100 | 85 | 78 | 81.5 |
| 2023 | 108 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 2 | 3 | 94 | 470 | 102 | 89 | 85 | 87.0 |
| 2023 | 109 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 2 | 4 | 94 | 445 | 105 | 94 | 83 | 88.5 |
| 2023 | 110 | 241 | 3 | CHULUCANAS | CHATO | KENT | 2 | 2 | 5 | 94 | 575 | 115 | 96 | 85 | 90.5 |
| 2023 | 111 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 1 | 1 | 123 | 489 | 110 | 95 | 83 | 89.0 |
| 2023 | 112 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 1 | 2 | 123 | 370 | 99 | 88 | 78 | 83.0 |
| 2023 | 113 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 1 | 3 | 123 | 472 | 108 | 93 | 82 | 87.5 |
| 2023 | 114 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 1 | 4 | 123 | 460 | 108 | 91 | 78 | 84.5 |
| 2023 | 115 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 1 | 5 | 123 | 391 | 103 | 89 | 77 | 83.0 |
| 2023 | 116 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 2 | 1 | 89 | 450 | 106 | 88 | 80 | 84.0 |
| 2023 | 117 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 2 | 2 | 89 | 535 | 107 | 98 | 89 | 93.5 |
| 2023 | 118 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 2 | 3 | 89 | 410 | 104 | 87 | 75 | 81.0 |
| 2023 | 119 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 2 | 4 | 89 | 490 | 106 | 95 | 83 | 89.0 |
| 2023 | 120 | 211 | 4 | CHATO | IRWIN | KENT | 2 | 2 | 5 | 89 | 376 | 98 | 88 | 74 | 81.0 |
| 2023 | 121 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 1 | 1 | 109 | 385 | 98 | 89 | 79 | 84.0 |
| 2023 | 122 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 1 | 2 | 109 | 400 | 100 | 85 | 80 | 82.5 |
| 2023 | 123 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 1 | 3 | 109 | 635 | 120 | 100 | 88 | 94.0 |
| 2023 | 124 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 1 | 4 | 109 | 616 | 123 | 93 | 81 | 87.0 |
| 2023 | 125 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 1 | 5 | 109 | 445 | 108 | 89 | 78 | 83.5 |
| 2023 | 126 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 2 | 1 | 63 | 585 | 120 | 96 | 81 | 88.5 |
| 2023 | 127 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 2 | 2 | 63 | 388 | 99 | 88 | 81 | 84.5 |
| 2023 | 128 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 2 | 3 | 63 | 717 | 129 | 106 | 87 | 96.5 |
| 2023 | 129 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 2 | 4 | 63 | 478 | 107 | 95 | 83 | 89.0 |
| 2023 | 130 | 131 | 5 | CHULUCANAS | JULIE | KENT | 2 | 2 | 5 | 63 | 445 | 108 | 89 | 78 | 83.5 |
| 2023 | 131 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 1 | 1 | 126 | 460 | 101 | 94 | 83 | 88.5 |
| 2023 | 132 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 1 | 2 | 126 | 440 | 99 | 89 | 86 | 87.5 |
| 2023 | 133 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 1 | 3 | 126 | 535 | 112 | 96 | 86 | 91.0 |
| 2023 | 134 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 1 | 4 | 126 | 560 | 118 | 95 | 87 | 91.0 |
| 2023 | 135 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 1 | 5 | 126 | 420 | 106 | 84 | 78 | 81.0 |
| 2023 | 136 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 2 | 1 | 56 | 380 | 100 | 84 | 77 | 80.5 |
| 2023 | 137 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 2 | 2 | 56 | 368 | 98 | 85 | 75 | 80.0 |
| 2023 | 138 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 2 | 3 | 56 | 500 | 114 | 92 | 84 | 88.0 |
| 2023 | 139 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 2 | 4 | 56 | 310 | 92 | 80 | 75 | 77.5 |
| 2023 | 140 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 2 | 2 | 5 | 56 | 400 | 100 | 84 | 79 | 81.5 |
| 2023 | 141 | 221 | 7 | CHATO | CHATO | KENT | 2 | 1 | 1 | 103 | 405 | 100 | 89 | 79 | 84.0 |
| 2023 | 142 | 221 | 7 | CHATO | CHATO | KENT | 2 | 1 | 2 | 103 | 460 | 107 | 90 | 83 | 86.5 |
| 2023 | 143 | 221 | 7 | CHATO | CHATO | KENT | 2 | 1 | 3 | 103 | 470 | 107 | 90 | 81 | 85.5 |
| 2023 | 144 | 221 | 7 | CHATO | CHATO | KENT | 2 | 1 | 4 | 103 | 410 | 105 | 88 | 74 | 81.0 |
| 2023 | 145 | 221 | 7 | CHATO | CHATO | KENT | 2 | 1 | 5 | 103 | 610 | 115 | 103 | 92 | 97.5 |
| 2023 | 146 | 221 | 7 | CHATO | CHATO | KENT | 2 | 2 | 1 | 124 | 470 | 111 | 92 | 79 | 85.5 |
| 2023 | 147 | 221 | 7 | CHATO | CHATO | KENT | 2 | 2 | 2 | 124 | 435 | 109 | 86 | 79 | 82.5 |
| 2023 | 148 | 221 | 7 | CHATO | CHATO | KENT | 2 | 2 | 3 | 124 | 445 | 107 | 85 | 80 | 82.5 |
| 2023 | 149 | 221 | 7 | CHATO | CHATO | KENT | 2 | 2 | 4 | 124 | 430 | 104 | 91 | 79 | 85.0 |
| 2023 | 150 | 221 | 7 | CHATO | CHATO | KENT | 2 | 2 | 5 | 124 | 639 | 115 | 99 | 90 | 94.5 |
| 2023 | 151 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 1 | 1 | 95 | 615 | 119 | 98 | 89 | 93.5 |
| 2023 | 152 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 1 | 2 | 95 | 430 | 103 | 92 | 82 | 87.0 |
| 2023 | 153 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 1 | 3 | 95 | 460 | 104 | 89 | 84 | 86.5 |
| 2023 | 154 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 1 | 4 | 95 | 391 | 94 | 92 | 82 | 87.0 |
| 2023 | 155 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 1 | 5 | 95 | 410 | 100 | 93 | 80 | 86.5 |
| 2023 | 156 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 2 | 1 | 79 | 489 | 109 | 87 | 83 | 85.0 |
| 2023 | 157 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 2 | 2 | 79 | 569 | 113 | 98 | 89 | 93.5 |
| 2023 | 158 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 2 | 3 | 79 | 566 | 116 | 95 | 84 | 89.5 |
| 2023 | 159 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 2 | 4 | 79 | 475 | 106 | 96 | 84 | 90.0 |
| 2023 | 160 | 121 | 8 | CHATO | CHULUCANAS | KENT | 2 | 2 | 5 | 79 | 490 | 110 | 91 | 82 | 86.5 |
| 2023 | 161 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 1 | 1 | 85 | 361 | 95 | 86 | 78 | 82.0 |
| 2023 | 162 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 1 | 2 | 85 | 460 | 105 | 93 | 81 | 87.0 |
| 2023 | 163 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 1 | 3 | 85 | 465 | 103 | 94 | 82 | 88.0 |
| 2023 | 164 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 1 | 4 | 85 | 450 | 108 | 84 | 80 | 82.0 |
| 2023 | 165 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 1 | 5 | 85 | 552 | 111 | 97 | 84 | 90.5 |
| 2023 | 166 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 2 | 1 | 113 | 351 | 96 | 84 | 77 | 80.5 |
| 2023 | 167 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 2 | 2 | 113 | 584 | 117 | 97 | 84 | 90.5 |
| 2023 | 168 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 2 | 3 | 113 | 440 | 109 | 89 | 77 | 83.0 |
| 2023 | 169 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 2 | 4 | 113 | 420 | 103 | 90 | 80 | 85.0 |
| 2023 | 170 | 141 | 1 | CHULUCANAS | CHULUCANAS | KENT | 3 | 2 | 5 | 113 | 361 | 100 | 86 | 72 | 79.0 |
| 2023 | 171 | 231 | 2 | CHATO | JULIE | KENT | 3 | 1 | 1 | 57 | 645 | 120 | 102 | 89 | 95.5 |
| 2023 | 172 | 231 | 2 | CHATO | JULIE | KENT | 3 | 1 | 2 | 57 | 440 | 105 | 83 | 79 | 81.0 |
| 2023 | 173 | 231 | 2 | CHATO | JULIE | KENT | 3 | 1 | 3 | 57 | 300 | 97 | 81 | 70 | 75.5 |
| 2023 | 174 | 231 | 2 | CHATO | JULIE | KENT | 3 | 1 | 4 | 57 | 495 | 113 | 96 | 81 | 88.5 |
| 2023 | 175 | 231 | 2 | CHATO | JULIE | KENT | 3 | 1 | 5 | 57 | 460 | 111 | 88 | 78 | 83.0 |
| 2023 | 176 | 231 | 2 | CHATO | JULIE | KENT | 3 | 2 | 1 | 53 | 360 | 102 | 89 | 72 | 80.5 |
| 2023 | 177 | 231 | 2 | CHATO | JULIE | KENT | 3 | 2 | 2 | 53 | 444 | 108 | 86 | 82 | 84.0 |
| 2023 | 178 | 231 | 2 | CHATO | JULIE | KENT | 3 | 2 | 3 | 53 | 489 | 112 | 91 | 83 | 87.0 |
| 2023 | 179 | 231 | 2 | CHATO | JULIE | KENT | 3 | 2 | 4 | 53 | 488 | 111 | 93 | 82 | 87.5 |
| 2023 | 180 | 231 | 2 | CHATO | JULIE | KENT | 3 | 2 | 5 | 53 | 400 | 101 | 87 | 79 | 83.0 |
| 2023 | 181 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 1 | 1 | 87 | 655 | 123 | 101 | 91 | 96.0 |
| 2023 | 182 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 1 | 2 | 87 | 392 | 103 | 88 | 78 | 83.0 |
| 2023 | 183 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 1 | 3 | 87 | 316 | 96 | 83 | 73 | 78.0 |
| 2023 | 184 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 1 | 4 | 87 | 420 | 101 | 86 | 83 | 84.5 |
| 2023 | 185 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 1 | 5 | 87 | 410 | 103 | 87 | 79 | 83.0 |
| 2023 | 186 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 2 | 1 | 64 | 490 | 108 | 88 | 82 | 85.0 |
| 2023 | 187 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 2 | 2 | 64 | 400 | 95 | 89 | 82 | 85.5 |
| 2023 | 188 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 2 | 3 | 64 | 575 | 112 | 96 | 89 | 92.5 |
| 2023 | 189 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 2 | 4 | 64 | 613 | 112 | 98 | 91 | 94.5 |
| 2023 | 190 | 241 | 3 | CHULUCANAS | CHATO | KENT | 3 | 2 | 5 | 64 | 410 | 103 | 88 | 80 | 84.0 |
| 2023 | 191 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 1 | 1 | 92 | 530 | 113 | 99 | 88 | 93.5 |
| 2023 | 192 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 1 | 2 | 92 | 391 | 101 | 90 | 77 | 83.5 |
| 2023 | 193 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 1 | 3 | 92 | 418 | 102 | 89 | 77 | 83.0 |
| 2023 | 194 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 1 | 4 | 92 | 450 | 100 | 87 | 83 | 85.0 |
| 2023 | 195 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 1 | 5 | 92 | 550 | 112 | 97 | 85 | 91.0 |
| 2023 | 196 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 2 | 1 | 96 | 510 | 112 | 93 | 80 | 86.5 |
| 2023 | 197 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 2 | 2 | 96 | 700 | 124 | 102 | 90 | 96.0 |
| 2023 | 198 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 2 | 3 | 96 | 470 | 104 | 89 | 87 | 88.0 |
| 2023 | 199 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 2 | 4 | 96 | 350 | 95 | 82 | 77 | 79.5 |
| 2023 | 200 | 211 | 4 | CHATO | IRWIN | KENT | 3 | 2 | 5 | 96 | 415 | 101 | 89 | 80 | 84.5 |
| 2023 | 201 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 1 | 1 | 64 | 450 | 108 | 91 | 78 | 84.5 |
| 2023 | 202 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 1 | 2 | 64 | 420 | 109 | 90 | 75 | 82.5 |
| 2023 | 203 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 1 | 3 | 64 | 640 | 120 | 104 | 90 | 97.0 |
| 2023 | 204 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 1 | 4 | 64 | 520 | 111 | 91 | 83 | 87.0 |
| 2023 | 205 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 1 | 5 | 64 | 625 | 126 | 95 | 86 | 90.5 |
| 2023 | 206 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 2 | 1 | 162 | 490 | 110 | 89 | 82 | 85.5 |
| 2023 | 207 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 2 | 2 | 162 | 515 | 107 | 92 | 84 | 88.0 |
| 2023 | 208 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 2 | 3 | 162 | 390 | 103 | 85 | 75 | 80.0 |
| 2023 | 209 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 2 | 4 | 162 | 465 | 105 | 89 | 80 | 84.5 |
| 2023 | 210 | 131 | 5 | CHULUCANAS | JULIE | KENT | 3 | 2 | 5 | 162 | 615 | 118 | 100 | 89 | 94.5 |
| 2023 | 211 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 1 | 1 | 128 | 465 | 105 | 90 | 80 | 85.0 |
| 2023 | 212 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 1 | 2 | 128 | 535 | 116 | 93 | 85 | 89.0 |
| 2023 | 213 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 1 | 3 | 128 | 375 | 100 | 85 | 76 | 80.5 |
| 2023 | 214 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 1 | 4 | 128 | 410 | 103 | 86 | 77 | 81.5 |
| 2023 | 215 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 1 | 5 | 128 | 435 | 109 | 87 | 81 | 84.0 |
| 2023 | 216 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 2 | 1 | 93 | 452 | 108 | 88 | 81 | 84.5 |
| 2023 | 217 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 2 | 2 | 93 | 540 | 117 | 92 | 84 | 88.0 |
| 2023 | 218 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 2 | 3 | 93 | 426 | 105 | 85 | 79 | 82.0 |
| 2023 | 219 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 2 | 4 | 93 | 366 | 106 | 84 | 75 | 79.5 |
| 2023 | 220 | 111 | 6 | CHULUCANAS | IRWIN | KENT | 3 | 2 | 5 | 93 | 435 | 108 | 93 | 78 | 85.5 |
| 2023 | 221 | 221 | 7 | CHATO | CHATO | KENT | 3 | 1 | 1 | 113 | 615 | 120 | 101 | 85 | 93.0 |
| 2023 | 222 | 221 | 7 | CHATO | CHATO | KENT | 3 | 1 | 2 | 113 | 505 | 113 | 90 | 80 | 85.0 |
| 2023 | 223 | 221 | 7 | CHATO | CHATO | KENT | 3 | 1 | 3 | 113 | 430 | 107 | 86 | 78 | 82.0 |
| 2023 | 224 | 221 | 7 | CHATO | CHATO | KENT | 3 | 1 | 4 | 113 | 475 | 106 | 92 | 83 | 87.5 |
| 2023 | 225 | 221 | 7 | CHATO | CHATO | KENT | 3 | 1 | 5 | 113 | 325 | 93 | 81 | 72 | 76.5 |
| 2023 | 226 | 221 | 7 | CHATO | CHATO | KENT | 3 | 2 | 1 | 99 | 470 | 106 | 89 | 82 | 85.5 |
| 2023 | 227 | 221 | 7 | CHATO | CHATO | KENT | 3 | 2 | 2 | 99 | 480 | 109 | 96 | 80 | 88.0 |
| 2023 | 228 | 221 | 7 | CHATO | CHATO | KENT | 3 | 2 | 3 | 99 | 525 | 109 | 97 | 85 | 91.0 |
| 2023 | 229 | 221 | 7 | CHATO | CHATO | KENT | 3 | 2 | 4 | 99 | 452 | 113 | 94 | 77 | 85.5 |
| 2023 | 230 | 221 | 7 | CHATO | CHATO | KENT | 3 | 2 | 5 | 99 | 416 | 101 | 89 | 82 | 85.5 |
| 2023 | 231 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 1 | 1 | 103 | 470 | 108 | 90 | 81 | 85.5 |
| 2023 | 232 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 1 | 2 | 103 | 410 | 105 | 88 | 76 | 82.0 |
| 2023 | 233 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 1 | 3 | 103 | 450 | 111 | 89 | 81 | 85.0 |
| 2023 | 234 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 1 | 4 | 103 | 620 | 119 | 100 | 86 | 93.0 |
| 2023 | 235 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 1 | 5 | 103 | |||||
| 2023 | 236 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 2 | 1 | 108 | 471 | 111 | 90 | 80 | 85.0 |
| 2023 | 237 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 2 | 2 | 108 | 475 | 110 | 93 | 81 | 87.0 |
| 2023 | 238 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 2 | 3 | 108 | 525 | 114 | 91 | 81 | 86.0 |
| 2023 | 239 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 2 | 4 | 108 | 426 | 100 | 86 | 82 | 84.0 |
| 2023 | 240 | 121 | 8 | CHATO | CHULUCANAS | KENT | 3 | 2 | 5 | 108 | 527 | 113 | 88 | 85 | 86.5 |
3 Data summary
Summary of the number of data points recorded for each treatment and evaluated variable.
sm <- rdt %>%
group_by(year, treat) %>%
summarise(across(height:sproud, ~ sum(!is.na(.))))
sm
## # A tibble: 24 × 6
## # Groups: year [3]
## year treat height n_fruits flowering sproud
## <fct> <fct> <int> <int> <int> <int>
## 1 2017 111 0 26 26 0
## 2 2017 121 0 26 26 0
## 3 2017 131 0 25 25 0
## 4 2017 141 0 26 26 0
## 5 2017 211 0 26 26 0
## 6 2017 221 0 26 26 0
## 7 2017 231 0 26 26 0
## 8 2017 241 0 27 27 0
## 9 2018 111 0 9 22 0
## 10 2018 121 0 9 23 0
## # ℹ 14 more rows
sm <- fru %>%
group_by(year, treat) %>%
summarise(across(weigth:diameter_average, ~ sum(!is.na(.))))
sm
## # A tibble: 8 × 7
## # Groups: year [1]
## year treat weigth long diameter_1 diameter_2 diameter_average
## <fct> <fct> <int> <int> <int> <int> <int>
## 1 2023 111 30 30 30 30 30
## 2 2023 121 29 29 29 29 29
## 3 2023 131 30 30 30 30 30
## 4 2023 141 30 30 30 30 30
## 5 2023 211 30 30 30 30 30
## 6 2023 221 30 30 30 30 30
## 7 2023 231 30 30 30 30 30
## 8 2023 241 30 30 30 30 304 Meteorological data
Climatic conditions of the study area located in the Tambogrande district, Piura region.
met <- range_read(ss = gs, sheet = "clima") %>%
mutate(date = as_date(Fecha))
scale <- 2
plot <- met %>%
ggplot(aes(x = date)) +
geom_line(aes(y = TMax, color = "Tmax (°C)"), size= 0.8, linetype = "longdash") +
geom_line(aes(y = TMin, color = "Tmin (°C)"), size= 0.8, linetype = "dotted") +
geom_bar(aes(y = PP/scale)
, stat="identity", size=.1, fill="blue", color="black", alpha=.4) +
geom_line(aes(y = HR/scale, color = "HR (%)"), size = 0.8, linetype = "twodash") +
scale_color_manual("", values = c("skyblue", "red", "blue")) +
scale_y_continuous(limits = c(0, 50)
, expand = c(0, 0)
, name = "Temperature (°C)"
, sec.axis = sec_axis(~ . * scale, name = "Precipitation (mm)")
) +
scale_x_date(date_breaks = "3 month", date_labels = "%b-%Y", name = NULL) +
theme_minimal_grid() +
theme(legend.position = "top") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
plot %>%
ggsave2(plot = ., "submission/Figure_2.jpg", units = "cm"
, width = 25, height = 15)
plot %>%
ggsave2(plot = ., "submission/Figure_2.eps", units = "cm"
, width = 25, height = 15)
knitr::include_graphics("submission/Figure_2.jpg")5 Objetives
Evaluate the effect of the rootstock-interstock interaction on the agronomic traits and fruit biometrics of the mango crop in the San Lorenzo Valley.
5.1 Specific Objective 1
Determine the effect of the rootstock-interstock interaction on the agronomic characteristics of mango.
5.1.1 Plant height
trait <- "height"
lmm <- paste({{trait}}, "~ 1 + (1|block) + stock*edge") %>% as.formula()
lmd <- paste({{trait}}, "~ block + stock*edge") %>% as.formula()
rmout <- rdt %>%
remove_outliers(formula = lmm
, drop_na = T, plot_diag = T)
rmout$diagplot
rmout$outliers
## index block stock edge height resi res_MAD rawp.BHStud
## 87 523 2 CHATO JULIE 2.00 -1.643199 -3.984232 0.00006769863
## 126 563 2 CHULUCANAS CHATO 1.90 -1.731293 -4.197830 0.00002694848
## 127 564 2 CHULUCANAS CHATO 1.85 -1.781293 -4.319064 0.00001566924
## adjp bholm out_flag
## 87 0.00006769863 0.013810521 OUTLIER
## 126 0.00002694848 0.005524438 OUTLIER
## 127 0.00001566924 0.003227863 OUTLIER
model <- rmout$data$clean %>%
aov(formula = lmd, .)
anova(model)
## Analysis of Variance Table
##
## Response: height
## Df Sum Sq Mean Sq F value Pr(>F)
## block 2 3.140 1.57012 9.1832 0.000155 ***
## stock 1 1.273 1.27268 7.4435 0.006954 **
## edge 3 1.994 0.66450 3.8865 0.009977 **
## stock:edge 3 2.301 0.76689 4.4853 0.004549 **
## Residuals 193 32.999 0.17098
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mc <- emmeans(model, ~ edge|stock) %>%
cld(Letters = letters, reversed = F) %>%
mutate(across(.group, trimws)) %>%
rename(group = ".group")
mc %>% kable()| edge | stock | emmean | SE | df | lower.CL | upper.CL | group | |
|---|---|---|---|---|---|---|---|---|
| 2 | CHULUCANAS | CHATO | 3.662963 | 0.0795773 | 193 | 3.506010 | 3.819916 | a |
| 1 | CHATO | CHATO | 3.741984 | 0.0811085 | 193 | 3.582011 | 3.901957 | a |
| 4 | JULIE | CHATO | 3.860337 | 0.0827154 | 193 | 3.697194 | 4.023479 | a |
| 3 | IRWIN | CHATO | 3.915061 | 0.0811085 | 193 | 3.755088 | 4.075034 | a |
| 8 | JULIE | CHULUCANAS | 3.467553 | 0.0844563 | 193 | 3.300977 | 3.634129 | a |
| 6 | CHULUCANAS | CHULUCANAS | 3.497320 | 0.0811085 | 193 | 3.337347 | 3.657293 | a |
| 7 | IRWIN | CHULUCANAS | 3.649114 | 0.0844563 | 193 | 3.482538 | 3.815690 | ab |
| 5 | CHATO | CHULUCANAS | 3.925048 | 0.0827647 | 193 | 3.761808 | 4.088287 | b |
p1a <- mc %>%
plot_smr(x = "stock"
, y = "emmean"
, group = "edge"
, sig = "group"
, error = "SE"
, color = T
, xlab = "Rootstock"
, ylab = "Plant height (m)"
, glab = "Interstock"
, ylimits = c(0, 6, 2)
,
)
p1a5.1.2 Sproud
trait <- "sproud"
lmm <- paste({{trait}}, "~ 1 + (1|block) + stock*edge") %>% as.formula()
lmd <- paste({{trait}}, "~ block + stock*edge") %>% as.formula()
rmout <- rdt %>%
remove_outliers(formula = lmm
, drop_na = T, plot_diag = T)
rmout$diagplot
rmout$outliers
## index block stock edge sproud resi res_MAD rawp.BHStud
## 8 441 1 CHULUCANAS CHULUCANAS 0 -63.26923 -4.267451 0.0000197719
## 126 567 2 CHULUCANAS CHATO 10 -58.26923 -3.930206 0.0000848732
## adjp bholm out_flag
## 8 0.0000197719 0.003974153 OUTLIER
## 126 0.0000848732 0.016974639 OUTLIER
model <- rmout$data$clean %>%
aov(formula = lmd, .)
anova(model)
## Analysis of Variance Table
##
## Response: sproud
## Df Sum Sq Mean Sq F value Pr(>F)
## block 2 362 180.9 0.5152 0.59820
## stock 1 6579 6578.9 18.7416 0.00002425 ***
## edge 3 2054 684.7 1.9506 0.12292
## stock:edge 3 2713 904.2 2.5758 0.05521 .
## Residuals 189 66345 351.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mc <- emmeans(model, ~ edge|stock) %>%
cld(Letters = letters, reversed = T) %>%
mutate(across(.group, trimws)) %>%
rename(group = ".group")
mc %>% kable()| edge | stock | emmean | SE | df | lower.CL | upper.CL | group | |
|---|---|---|---|---|---|---|---|---|
| 4 | CHULUCANAS | CHATO | 65.17927 | 3.675132 | 189 | 57.92972 | 72.42882 | a |
| 3 | CHATO | CHATO | 54.81356 | 3.747943 | 189 | 47.42039 | 62.20674 | a |
| 1 | IRWIN | CHATO | 52.08471 | 3.750192 | 189 | 44.68710 | 59.48232 | a |
| 2 | JULIE | CHATO | 51.91004 | 3.675132 | 189 | 44.66049 | 59.15959 | a |
| 7 | JULIE | CHULUCANAS | 72.15745 | 3.826839 | 189 | 64.60864 | 79.70625 | a |
| 6 | CHATO | CHULUCANAS | 70.57288 | 3.750234 | 189 | 63.17519 | 77.97057 | a |
| 5 | CHULUCANAS | CHULUCANAS | 65.94241 | 3.750188 | 189 | 58.54481 | 73.34001 | a |
| 8 | IRWIN | CHULUCANAS | 61.21227 | 3.910119 | 189 | 53.49919 | 68.92535 | a |
p1b <- mc %>%
plot_smr(x = "stock"
, y = "emmean"
, group = "edge"
, sig = "group"
, error = "SE"
, color = T
, xlab = "Rootstock"
, ylab = "Sproud ('%')"
, glab = "Interstock"
, ylimits = c(0, 100, 20)
)
p1b 5.1.3 Number of fruits
trait <- "n_fruits"
lmm <- paste({{trait}}, "~ 1 + (1|block) + year + stock*edge + (1 + year|treat)") %>% as.formula()
lmd <- paste({{trait}}, "~ block + year + stock*edge") %>% as.formula()
rmout <- rdt %>%
remove_outliers(formula = lmm
, drop_na = T, plot_diag = T)
rmout$diagplot
rmout$outliers
## index block year stock edge treat n_fruits resi res_MAD rawp.BHStud
## 442 604 3 2019 CHATO JULIE 231 539 287.2486 4.008689 0.00006105685
## adjp bholm out_flag
## 442 0.00006105685 0.02955151 OUTLIER
model <- rmout$data$clean %>%
aov(formula = lmd, .)
anova(model)
## Analysis of Variance Table
##
## Response: n_fruits
## Df Sum Sq Mean Sq F value Pr(>F)
## block 2 261207 130604 21.6839 0.0000000009805 ***
## year 2 126248 63124 10.4804 0.0000352211768 ***
## stock 1 9326 9326 1.5483 0.2140
## edge 3 22131 7377 1.2248 0.3001
## stock:edge 3 15548 5183 0.8605 0.4615
## Residuals 471 2836870 6023
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mc <- emmeans(model, ~ year|edge|stock) %>%
cld(Letters = letters, reversed = T) %>%
mutate(across(.group, trimws)) %>%
rename(group = ".group")
mc %>% kable()| year | edge | stock | emmean | SE | df | lower.CL | upper.CL | group | |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 2018 | CHATO | CHATO | 197.2613 | 13.04649 | 471 | 171.6248 | 222.8978 | a |
| 3 | 2019 | CHATO | CHATO | 194.2890 | 10.75243 | 471 | 173.1603 | 215.4177 | a |
| 2 | 2017 | CHATO | CHATO | 162.5132 | 10.74838 | 471 | 141.3925 | 183.6339 | b |
| 13 | 2018 | CHATO | CHULUCANAS | 205.1341 | 12.95537 | 471 | 179.6767 | 230.5916 | a |
| 15 | 2019 | CHATO | CHULUCANAS | 202.1618 | 10.59847 | 471 | 181.3357 | 222.9880 | a |
| 14 | 2017 | CHATO | CHULUCANAS | 170.3860 | 10.59352 | 471 | 149.5696 | 191.2024 | b |
| 4 | 2018 | CHULUCANAS | CHATO | 206.5226 | 13.04648 | 471 | 180.8861 | 232.1591 | a |
| 6 | 2019 | CHULUCANAS | CHATO | 203.5503 | 10.75303 | 471 | 182.4205 | 224.6802 | a |
| 5 | 2017 | CHULUCANAS | CHATO | 171.7745 | 10.74778 | 471 | 150.6550 | 192.8940 | b |
| 16 | 2018 | CHULUCANAS | CHULUCANAS | 233.6210 | 13.04648 | 471 | 207.9845 | 259.2575 | a |
| 18 | 2019 | CHULUCANAS | CHULUCANAS | 230.6487 | 10.75303 | 471 | 209.5188 | 251.7785 | a |
| 17 | 2017 | CHULUCANAS | CHULUCANAS | 198.8729 | 10.74778 | 471 | 177.7533 | 219.9924 | b |
| 7 | 2018 | IRWIN | CHATO | 213.0482 | 13.04649 | 471 | 187.4117 | 238.6847 | a |
| 9 | 2019 | IRWIN | CHATO | 210.0759 | 10.75243 | 471 | 188.9472 | 231.2046 | a |
| 8 | 2017 | IRWIN | CHATO | 178.3001 | 10.74838 | 471 | 157.1794 | 199.4208 | b |
| 19 | 2018 | IRWIN | CHULUCANAS | 209.5332 | 13.19501 | 471 | 183.6048 | 235.4616 | a |
| 21 | 2019 | IRWIN | CHULUCANAS | 206.5609 | 11.07069 | 471 | 184.8068 | 228.3150 | a |
| 20 | 2017 | IRWIN | CHULUCANAS | 174.7851 | 10.92618 | 471 | 153.3150 | 196.2552 | b |
| 10 | 2018 | JULIE | CHATO | 207.7604 | 13.14195 | 471 | 181.9362 | 233.5845 | a |
| 12 | 2019 | JULIE | CHATO | 204.7881 | 10.95974 | 471 | 183.2520 | 226.3241 | a |
| 11 | 2017 | JULIE | CHATO | 173.0122 | 10.86339 | 471 | 151.6655 | 194.3589 | b |
| 22 | 2018 | JULIE | CHULUCANAS | 211.3414 | 13.14337 | 471 | 185.5145 | 237.1683 | a |
| 24 | 2019 | JULIE | CHULUCANAS | 208.3691 | 10.91480 | 471 | 186.9214 | 229.8169 | a |
| 23 | 2017 | JULIE | CHULUCANAS | 176.5933 | 10.91078 | 471 | 155.1535 | 198.0331 | b |
p1c <- mc %>%
plot_smr(type = "bar"
, x = "year"
, y = "emmean"
, group = "edge"
, sig = "group"
, error = "SE"
, color = T
, xlab = "Year"
, ylab = "Fruits number"
, glab = "Interstock"
, ylimits = c(0, 320, 60)
) +
facet_wrap(. ~ stock, nrow = 2)
p1c 5.1.4 Flowering
trait <- "flowering"
lmm <- paste({{trait}}, "~ 1 + (1|block) + year + stock*edge + (1 + year|treat)") %>% as.formula()
lmd <- paste({{trait}}, "~ block + year + stock*edge") %>% as.formula()
rmout <- rdt %>%
remove_outliers(formula = lmm
, drop_na = T, plot_diag = T)
rmout$diagplot
rmout$outliers
## index block year stock edge treat flowering resi res_MAD
## 28 31 1 2017 CHATO IRWIN 211 5 -68.74456 -6.212394
## 32 35 1 2017 CHATO IRWIN 211 25 -48.74456 -4.405009
## 33 36 1 2017 CHATO IRWIN 211 25 -48.74456 -4.405009
## 64 67 1 2017 CHATO CHATO 221 20 -56.92226 -5.144022
## 65 68 1 2017 CHATO CHATO 221 30 -46.92226 -4.240330
## 67 70 1 2017 CHATO CHATO 221 15 -61.92226 -5.595869
## 69 72 1 2017 CHATO CHATO 221 15 -61.92226 -5.595869
## 127 131 2 2017 CHULUCANAS CHATO 241 25 -58.44225 -5.281382
## 166 171 3 2017 CHULUCANAS CHULUCANAS 141 20 -58.28192 -5.266893
## 213 225 1 2018 CHULUCANAS CHULUCANAS 141 20 -57.68630 -5.213068
## 232 258 1 2018 CHULUCANAS JULIE 131 10 -56.04249 -5.064518
## 243 273 1 2018 CHULUCANAS IRWIN 111 15 -58.16121 -5.255986
## 250 284 1 2018 CHATO CHATO 221 90 47.03144 4.250196
## 251 288 1 2018 CHATO CHATO 221 97 54.03144 4.882781
## 254 292 2 2018 CHATO IRWIN 211 5 -63.87075 -5.771952
## 289 328 2 2018 CHATO CHATO 221 3 -43.83305 -3.961160
## 292 331 2 2018 CHATO CHATO 221 0 -46.83305 -4.232268
## 298 338 2 2018 CHULUCANAS IRWIN 111 10 -67.02571 -6.057063
## 299 339 2 2018 CHULUCANAS IRWIN 111 5 -72.02571 -6.508909
## 311 352 2 2018 CHULUCANAS JULIE 131 20 -49.90698 -4.510056
## 333 376 3 2018 CHATO IRWIN 211 20 -44.36027 -4.008804
## 342 385 3 2018 CHULUCANAS CHULUCANAS 141 0 -77.04031 -6.962075
## 346 389 3 2018 CHATO JULIE 231 0 -47.63760 -4.304974
## 347 390 3 2018 CHATO JULIE 231 0 -47.63760 -4.304974
## 349 392 3 2018 CHATO JULIE 231 2 -45.63760 -4.124236
## 375 421 3 2018 CHULUCANAS JULIE 131 10 -55.39650 -5.006140
## 376 422 3 2018 CHULUCANAS JULIE 131 20 -45.39650 -4.102448
## 454 505 2 2019 CHATO IRWIN 211 30 -48.76953 -4.407266
## 526 581 3 2019 CHATO CHULUCANAS 121 7 -70.54614 -6.375202
## rawp.BHStud adjp bholm out_flag
## 28 0.000000000521833021 0.000000000521833021 0.000000305794150 OUTLIER
## 32 0.000010577939756562 0.000010577939756562 0.006040003600997 OUTLIER
## 33 0.000010577939756562 0.000010577939756562 0.006040003600997 OUTLIER
## 64 0.000000268917649482 0.000000268917649482 0.000155165483751 OUTLIER
## 65 0.000022319169655338 0.000022319169655338 0.012632650024921 OUTLIER
## 67 0.000000021952000884 0.000000021952000884 0.000012798016515 OUTLIER
## 69 0.000000021952000884 0.000000021952000884 0.000012798016515 OUTLIER
## 127 0.000000128212855666 0.000000128212855666 0.000074491669142 OUTLIER
## 166 0.000000138751758749 0.000000138751758749 0.000080476020075 OUTLIER
## 213 0.000000185743196379 0.000000185743196379 0.000107359567507 OUTLIER
## 232 0.000000409435427784 0.000000409435427784 0.000235834806404 OUTLIER
## 243 0.000000147233846226 0.000000147233846226 0.000085248396965 OUTLIER
## 250 0.000021358339519217 0.000021358339519217 0.012110178507396 OUTLIER
## 251 0.000001046000612570 0.000001046000612570 0.000600404351615 OUTLIER
## 254 0.000000007835861071 0.000000007835861071 0.000004576142866 OUTLIER
## 289 0.000074586480278027 0.000074586480278027 0.041843015435973 OUTLIER
## 292 0.000023134658141855 0.000023134658141855 0.013071081850148 OUTLIER
## 298 0.000000001386292858 0.000000001386292858 0.000000810981322 OUTLIER
## 299 0.000000000075698336 0.000000000075698336 0.000000044510622 OUTLIER
## 311 0.000006481038199890 0.000006481038199890 0.003713634888537 OUTLIER
## 333 0.000061026989556012 0.000061026989556012 0.034297168130479 OUTLIER
## 342 0.000000000003352874 0.000000000003352874 0.000000001974843 OUTLIER
## 346 0.000016700498484123 0.000016700498484123 0.009502583637466 OUTLIER
## 347 0.000016700498484123 0.000016700498484123 0.009502583637466 OUTLIER
## 349 0.000037196739853362 0.000037196739853362 0.020978961277296 OUTLIER
## 375 0.000000555322711371 0.000000555322711371 0.000319310559038 OUTLIER
## 376 0.000040880207851313 0.000040880207851313 0.023015557020289 OUTLIER
## 454 0.000010468378508710 0.000010468378508710 0.005987912506982 OUTLIER
## 526 0.000000000182721394 0.000000000182721394 0.000000107257458 OUTLIER
model <- rmout$data$clean %>%
aov(formula = lmd, .)
anova(model)
## Analysis of Variance Table
##
## Response: flowering
## Df Sum Sq Mean Sq F value Pr(>F)
## block 2 1978 988.9 3.3541 0.03566 *
## year 2 16473 8236.6 27.9371 0.000000000002796 ***
## stock 1 804 803.6 2.7257 0.09932 .
## edge 3 7276 2425.3 8.2263 0.000023116374039 ***
## stock:edge 3 1580 526.5 1.7859 0.14874
## Residuals 548 161564 294.8
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mc <- emmeans(model, ~ year|edge|stock) %>%
cld(Letters = letters, reversed = T) %>%
mutate(across(.group, trimws)) %>%
rename(group = ".group")
mc %>% kable()| year | edge | stock | emmean | SE | df | lower.CL | upper.CL | group | |
|---|---|---|---|---|---|---|---|---|---|
| 2 | 2019 | CHATO | CHATO | 77.01196 | 2.305001 | 548 | 72.48424 | 81.53968 | a |
| 1 | 2017 | CHATO | CHATO | 76.99530 | 2.345782 | 548 | 72.38748 | 81.60313 | a |
| 3 | 2018 | CHATO | CHATO | 64.90407 | 2.425731 | 548 | 60.13920 | 69.66894 | b |
| 14 | 2019 | CHATO | CHULUCANAS | 77.06506 | 2.198633 | 548 | 72.74628 | 81.38384 | a |
| 13 | 2017 | CHATO | CHULUCANAS | 77.04841 | 2.208166 | 548 | 72.71090 | 81.38591 | a |
| 15 | 2018 | CHATO | CHULUCANAS | 64.95718 | 2.269647 | 548 | 60.49890 | 69.41545 | b |
| 5 | 2019 | CHULUCANAS | CHATO | 87.26768 | 2.233767 | 548 | 82.87988 | 91.65547 | a |
| 4 | 2017 | CHULUCANAS | CHATO | 87.25102 | 2.226577 | 548 | 82.87735 | 91.62469 | a |
| 6 | 2018 | CHULUCANAS | CHATO | 75.15979 | 2.289284 | 548 | 70.66294 | 79.65663 | b |
| 17 | 2019 | CHULUCANAS | CHULUCANAS | 85.98612 | 2.243058 | 548 | 81.58008 | 90.39217 | a |
| 16 | 2017 | CHULUCANAS | CHULUCANAS | 85.96947 | 2.254128 | 548 | 81.54168 | 90.39726 | a |
| 18 | 2018 | CHULUCANAS | CHULUCANAS | 73.87824 | 2.329225 | 548 | 69.30293 | 78.45354 | b |
| 8 | 2019 | IRWIN | CHATO | 81.00814 | 2.291841 | 548 | 76.50627 | 85.51001 | a |
| 7 | 2017 | IRWIN | CHATO | 80.99148 | 2.311773 | 548 | 76.45046 | 85.53250 | a |
| 9 | 2018 | IRWIN | CHATO | 68.90025 | 2.375187 | 548 | 64.23467 | 73.56584 | b |
| 20 | 2019 | IRWIN | CHULUCANAS | 86.70568 | 2.312242 | 548 | 82.16374 | 91.24763 | a |
| 19 | 2017 | IRWIN | CHULUCANAS | 86.68903 | 2.284768 | 548 | 82.20105 | 91.17700 | a |
| 21 | 2018 | IRWIN | CHULUCANAS | 74.59780 | 2.389683 | 548 | 69.90374 | 79.29186 | b |
| 11 | 2019 | JULIE | CHATO | 78.22556 | 2.271401 | 548 | 73.76384 | 82.68728 | a |
| 10 | 2017 | JULIE | CHATO | 78.20890 | 2.263368 | 548 | 73.76296 | 82.65484 | a |
| 12 | 2018 | JULIE | CHATO | 66.11767 | 2.367724 | 548 | 61.46675 | 70.76860 | b |
| 23 | 2019 | JULIE | CHULUCANAS | 84.56367 | 2.325199 | 548 | 79.99628 | 89.13107 | a |
| 22 | 2017 | JULIE | CHULUCANAS | 84.54702 | 2.315901 | 548 | 79.99789 | 89.09615 | a |
| 24 | 2018 | JULIE | CHULUCANAS | 72.45579 | 2.429118 | 548 | 67.68427 | 77.22731 | b |
p1d <- mc %>%
plot_smr(type = "bar"
, x = "year"
, y = "emmean"
, group = "edge"
, sig = "group"
, error = "SE"
, color = T
, xlab = "Year"
, ylab = "Flowering ('%')"
, glab = "Interstock"
, ylimits = c(0, 120, 20)
) +
facet_wrap(. ~ stock, nrow = 2)
p1d5.1.5 Figure 3
Univariate analysis of the variables that determine the agronomic characteristics of mango.
legend <- cowplot::get_plot_component(p1a, 'guide-box-top', return_all = TRUE)
p1 <- list(p1a + theme(legend.position="none")
, p1b + theme(legend.position="none")
, p1c + theme(legend.position="none")
, p1d + theme(legend.position="none")
) %>%
plot_grid(plotlist = ., ncol = 2
, labels = "auto"
, rel_heights = c(1, 2)
)
fig <- plot_grid(legend, p1, ncol = 1, align = 'v', rel_heights = c(0.05, 1))
fig %>%
ggsave2(plot = ., "submission/Figure_3.jpg"
, units = "cm"
, width = 24
, height = 16
)
fig %>%
ggsave2(plot = ., "submission/Figure_3.eps"
, units = "cm"
, width = 24
, height = 16
)
knitr::include_graphics("submission/Figure_3.jpg")5.1.6 Multivariate
Principal Component Analysis (PCA) of agronomic traits in the mango crop based on the use of rootstock-interstock combinations.
mv <- rdt %>%
group_by(stock, edge) %>%
summarise(across(where(is.numeric), ~ mean(., na.rm = T))) %>%
unite("treat", stock:edge, sep = "-") %>%
rename(Treat = treat
, Height = height
, Fruits = n_fruits
, Flowering = flowering
, Sproud = sproud)
pca <- mv %>%
PCA(scale.unit = T, quali.sup = 1, graph = F)
# summary
summary(pca, nbelements = Inf, nb.dec = 2)
##
## Call:
## PCA(X = ., scale.unit = T, quali.sup = 1, graph = F)
##
##
## Eigenvalues
## Dim.1 Dim.2 Dim.3 Dim.4
## Variance 2.49 0.93 0.37 0.21
## % of var. 62.27 23.26 9.22 5.26
## Cumulative % of var. 62.27 85.52 94.74 100.00
##
## Individuals
## Dist Dim.1 ctr cos2 Dim.2 ctr cos2 Dim.3
## 1 | 2.28 | -1.99 19.84 0.76 | -0.72 7.04 0.10 | -0.43
## 2 | 1.67 | 1.05 5.51 0.39 | -0.61 4.97 0.13 | 1.15
## 3 | 2.18 | -1.90 18.19 0.76 | 0.89 10.71 0.17 | 0.36
## 4 | 1.74 | -1.44 10.38 0.68 | 0.94 11.90 0.29 | -0.19
## 5 | 1.52 | -0.49 1.23 0.11 | -1.05 14.72 0.47 | -0.41
## 6 | 2.83 | 2.26 25.69 0.64 | 1.63 35.67 0.33 | -0.51
## 7 | 1.00 | 0.68 2.34 0.46 | -0.03 0.01 0.00 | 0.67
## 8 | 2.21 | 1.83 16.82 0.69 | -1.06 14.98 0.23 | -0.63
## ctr cos2
## 1 6.36 0.04 |
## 2 44.91 0.47 |
## 3 4.40 0.03 |
## 4 1.21 0.01 |
## 5 5.78 0.07 |
## 6 8.90 0.03 |
## 7 15.00 0.44 |
## 8 13.43 0.08 |
##
## Variables
## Dim.1 ctr cos2 Dim.2 ctr cos2 Dim.3 ctr
## Height | -0.91 33.26 0.83 | 0.07 0.53 0.00 | 0.25 17.31
## Fruits | 0.57 13.26 0.33 | 0.78 66.19 0.62 | -0.16 6.81
## Flowering | 0.86 29.71 0.74 | 0.05 0.23 0.00 | 0.51 69.79
## Sproud | 0.77 23.77 0.59 | -0.55 33.05 0.31 | -0.15 6.10
## cos2
## Height 0.06 |
## Fruits 0.03 |
## Flowering 0.26 |
## Sproud 0.02 |
##
## Supplementary categories
## Dist Dim.1 cos2 v.test Dim.2 cos2 v.test Dim.3
## CHATO-CHATO | 2.28 | -1.99 0.76 -1.26 | -0.72 0.10 -0.75 | -0.43
## CHATO-CHULUCANAS | 1.67 | 1.05 0.39 0.66 | -0.61 0.13 -0.63 | 1.15
## CHATO-IRWIN | 2.18 | -1.90 0.76 -1.21 | 0.89 0.17 0.93 | 0.36
## CHATO-JULIE | 1.74 | -1.44 0.68 -0.91 | 0.94 0.29 0.98 | -0.19
## CHULUCANAS-CHATO | 1.52 | -0.49 0.11 -0.31 | -1.05 0.47 -1.09 | -0.41
## CHULUCANAS-CHULUCANAS | 2.83 | 2.26 0.64 1.43 | 1.63 0.33 1.69 | -0.51
## CHULUCANAS-IRWIN | 1.00 | 0.68 0.46 0.43 | -0.03 0.00 -0.03 | 0.67
## CHULUCANAS-JULIE | 2.21 | 1.83 0.69 1.16 | -1.06 0.23 -1.09 | -0.63
## cos2 v.test
## CHATO-CHATO 0.04 -0.71 |
## CHATO-CHULUCANAS 0.47 1.90 |
## CHATO-IRWIN 0.03 0.59 |
## CHATO-JULIE 0.01 -0.31 |
## CHULUCANAS-CHATO 0.07 -0.68 |
## CHULUCANAS-CHULUCANAS 0.03 -0.84 |
## CHULUCANAS-IRWIN 0.44 1.10 |
## CHULUCANAS-JULIE 0.08 -1.04 |
f2a <- plot.PCA(x = pca, choix = "var"
, cex=0.8
, label = "var"
)
f2b <- plot.PCA(x = pca, choix = "ind"
, habillage = 1
, invisible = c("ind")
, cex=0.8
) 5.1.7 Figure 4
Principal Component Analysis (PCA).
fig <- list(f2a, f2b) %>%
plot_grid(plotlist = ., ncol = 2, nrow = 1
, labels = "auto"
, rel_widths = c(1, 1.5)
)
fig %>%
ggsave2(plot = ., "submission/Figure_4.jpg", units = "cm"
, width = 25, height = 10
)
fig %>%
ggsave2(plot = ., "submission/Figure_4.eps", units = "cm"
, width = 25, height = 10
)
knitr::include_graphics("submission/Figure_4.jpg")5.1.8 Supplementary Figure 1
Results of the contributions and correlation of the variables in the Principal Component Analysis (PCA).
var <- get_pca_var(pca)
pt1 <- fviz_eig(pca,
addlabels=TRUE,
hjust = 0.05,
barfill="white",
barcolor ="darkblue",
linecolor ="red") +
ylim(0, 80) +
labs(
title = "PCA - percentage of explained variances",
y = "Variance (%)") +
theme_minimal()
pt2 <- fviz_contrib(pca,
choice = "var",
axes = 1,
top = 10,
fill="white",
color ="darkblue",
sort.val = "desc") +
ylim(0, 50) +
labs(title = "Dim 1 - variables contribution")
pt3 <- fviz_contrib(pca,
choice = "var",
axes = 2,
top = 10,
fill="white",
color ="darkblue",
sort.val = "desc") +
ylim(0, 80) +
labs(title = "Dim 2 - variables contribution")
pt4 <- ~ {
corrplot(var$cor,
method="number",
tl.col="black",
tl.srt=45,
)
}
plot <- list(pt1, pt2, pt3) %>%
plot_grid(plotlist = ., ncol = 1, labels = "auto") %>%
list(., pt4) %>%
plot_grid(plotlist = ., ncol = 2, labels = c("", "d"))
ggsave2(plot = plot, "submission/FigS1.jpg", height = 20, width = 28, units = "cm")
ggsave2(plot = plot, "submission/FigS1.eps", height = 20, width = 28, units = "cm")
knitr::include_graphics("submission/FigS1.jpg")5.2 Specific Objective 2
Determine the effect of the rootstock-interstock interaction on the fruit biometrics of mango.
5.2.1 Fruit Weigth
trait <- "weigth"
lmm <- paste({{trait}}, "~ 1 + (1|block) + stock*edge") %>% as.formula()
lmd <- paste({{trait}}, "~ block + stock*edge") %>% as.formula()
rmout <- fru %>%
remove_outliers(formula = lmm
, drop_na = T, plot_diag = T)
rmout$diagplot
rmout$outliers
## [1] index block stock edge weigth resi
## [7] res_MAD rawp.BHStud adjp bholm out_flag
## <0 rows> (o 0- extensión row.names)
model <- rmout$data$clean %>%
aov(formula = lmd, .)
anova(model)
## Analysis of Variance Table
##
## Response: weigth
## Df Sum Sq Mean Sq F value Pr(>F)
## block 2 73498 36749 4.6207 0.01078 *
## stock 1 1816 1816 0.2284 0.63320
## edge 3 4318 1439 0.1810 0.90923
## stock:edge 3 37870 12623 1.5872 0.19323
## Residuals 229 1821257 7953
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mc <- emmeans(model, ~ edge|stock) %>%
cld(Letters = letters, reversed = T) %>%
mutate(across(.group, trimws)) %>%
rename(group = ".group")
mc %>% kable()| edge | stock | emmean | SE | df | lower.CL | upper.CL | group | |
|---|---|---|---|---|---|---|---|---|
| 1 | IRWIN | CHATO | 482.0333 | 16.28198 | 229 | 449.9517 | 514.1150 | a |
| 2 | JULIE | CHATO | 465.9667 | 16.28198 | 229 | 433.8850 | 498.0483 | a |
| 4 | CHULUCANAS | CHATO | 462.3661 | 16.56272 | 229 | 429.7313 | 495.0009 | a |
| 3 | CHATO | CHATO | 452.5333 | 16.28198 | 229 | 420.4517 | 484.6150 | a |
| 7 | CHATO | CHULUCANAS | 484.9667 | 16.28198 | 229 | 452.8850 | 517.0483 | a |
| 6 | JULIE | CHULUCANAS | 484.7000 | 16.28198 | 229 | 452.6184 | 516.7816 | a |
| 8 | CHULUCANAS | CHULUCANAS | 468.1667 | 16.28198 | 229 | 436.0850 | 500.2483 | a |
| 5 | IRWIN | CHULUCANAS | 447.2333 | 16.28198 | 229 | 415.1517 | 479.3150 | a |
p2a <- mc %>%
plot_smr(x = "stock"
, y = "emmean"
, group = "edge"
, sig = "group"
, error = "SE"
, color = T
, xlab = "Rootstock"
, ylab = "Fruit Weigth (g)"
, glab = "Interstock"
, ylimits = c(0, 600, 100)
,
)
p2a5.2.2 Fruit length
trait <- "long"
lmm <- paste({{trait}}, "~ 1 + (1|block) + stock*edge") %>% as.formula()
lmd <- paste({{trait}}, "~ block + stock*edge") %>% as.formula()
rmout <- fru %>%
remove_outliers(formula = lmm
, drop_na = T, plot_diag = T)
rmout$diagplot
rmout$outliers
## [1] index block stock edge long resi
## [7] res_MAD rawp.BHStud adjp bholm out_flag
## <0 rows> (o 0- extensión row.names)
model <- rmout$data$clean %>%
aov(formula = lmd, .)
anova(model)
## Analysis of Variance Table
##
## Response: long
## Df Sum Sq Mean Sq F value Pr(>F)
## block 2 681.4 340.70 5.9312 0.003081 **
## stock 1 31.2 31.16 0.5424 0.462192
## edge 3 270.1 90.02 1.5672 0.198107
## stock:edge 3 39.5 13.15 0.2289 0.876184
## Residuals 229 13154.4 57.44
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mc <- emmeans(model, ~ edge|stock) %>%
cld(Letters = letters, reversed = T) %>%
mutate(across(.group, trimws)) %>%
rename(group = ".group")
mc %>% kable()| edge | stock | emmean | SE | df | lower.CL | upper.CL | group | |
|---|---|---|---|---|---|---|---|---|
| 1 | JULIE | CHATO | 107.6667 | 1.383746 | 229 | 104.9402 | 110.3932 | a |
| 3 | CHULUCANAS | CHATO | 106.3048 | 1.407606 | 229 | 103.5313 | 109.0783 | a |
| 2 | IRWIN | CHATO | 106.0667 | 1.383746 | 229 | 103.3402 | 108.7932 | a |
| 4 | CHATO | CHATO | 105.9667 | 1.383746 | 229 | 103.2402 | 108.6932 | a |
| 6 | JULIE | CHULUCANAS | 109.7333 | 1.383746 | 229 | 107.0068 | 112.4598 | a |
| 7 | CHATO | CHULUCANAS | 106.5333 | 1.383746 | 229 | 103.8068 | 109.2598 | a |
| 5 | IRWIN | CHULUCANAS | 106.4333 | 1.383746 | 229 | 103.7068 | 109.1598 | a |
| 8 | CHULUCANAS | CHULUCANAS | 106.2000 | 1.383746 | 229 | 103.4735 | 108.9265 | a |
p2b <- mc %>%
plot_smr(x = "stock"
, y = "emmean"
, group = "edge"
, sig = "group"
, error = "SE"
, color = T
, xlab = "Rootstock"
, ylab = "Fruit length (mm)"
, glab = "Interstock"
, ylimits = c(0, 120, 20)
,
)
p2b5.2.3 Fruit diameter
trait <- "diameter_average"
lmm <- paste({{trait}}, "~ 1 + (1|block) + stock*edge") %>% as.formula()
lmd <- paste({{trait}}, "~ block + stock*edge") %>% as.formula()
rmout <- fru %>%
remove_outliers(formula = lmm
, drop_na = T, plot_diag = T)
rmout$diagplot
rmout$outliers
## [1] index block stock edge
## [5] diameter_average resi res_MAD rawp.BHStud
## [9] adjp bholm out_flag
## <0 rows> (o 0- extensión row.names)
model <- rmout$data$clean %>%
aov(formula = lmd, .)
anova(model)
## Analysis of Variance Table
##
## Response: diameter_average
## Df Sum Sq Mean Sq F value Pr(>F)
## block 2 248.1 124.033 5.0489 0.007149 **
## stock 1 1.2 1.178 0.0480 0.826864
## edge 3 6.1 2.027 0.0825 0.969504
## stock:edge 3 234.3 78.109 3.1796 0.024804 *
## Residuals 229 5625.6 24.566
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
mc <- emmeans(model, ~ edge|stock) %>%
cld(Letters = letters, reversed = T) %>%
mutate(across(.group, trimws)) %>%
rename(group = ".group")
mc %>% kable()| edge | stock | emmean | SE | df | lower.CL | upper.CL | group | |
|---|---|---|---|---|---|---|---|---|
| 1 | IRWIN | CHATO | 87.63333 | 0.9049151 | 229 | 85.85031 | 89.41636 | a |
| 2 | JULIE | CHATO | 86.23333 | 0.9049151 | 229 | 84.45031 | 88.01636 | a |
| 4 | CHULUCANAS | CHATO | 86.07080 | 0.9205182 | 229 | 84.25703 | 87.88457 | a |
| 3 | CHATO | CHATO | 85.23333 | 0.9049151 | 229 | 83.45031 | 87.01636 | a |
| 7 | CHATO | CHULUCANAS | 87.70000 | 0.9049151 | 229 | 85.91698 | 89.48302 | a |
| 6 | JULIE | CHULUCANAS | 86.30000 | 0.9049151 | 229 | 84.51698 | 88.08302 | a |
| 8 | CHULUCANAS | CHULUCANAS | 86.08333 | 0.9049151 | 229 | 84.30031 | 87.86636 | a |
| 5 | IRWIN | CHULUCANAS | 84.53333 | 0.9049151 | 229 | 82.75031 | 86.31636 | a |
p2c <- mc %>%
plot_smr(x = "stock"
, y = "emmean"
, group = "edge"
, sig = "group"
, error = "SE"
, color = T
, xlab = "Rootstock"
, ylab = "Fruit diameter (mm)"
, glab = "Interstock"
, ylimits = c(0, 100, 20)
,
)
p2c5.2.4 Table 2
Descriptive statistics of the variables that determine the fruit biometrics of mango.
sts <- Summarize(weigth ~ stock*edge, data = fru, digits = 2, na.rm = TRUE)
tb1a <- sts%>%
merge(., mc) %>%
mutate(Variable = "Fruit Weigth (g)") %>%
dplyr::select(Variable, stock, edge, mean, sd, min, max, group) %>%
rename(Rootstock = stock,
Interstock = edge,
Sig = group)
sts <- Summarize(long ~ stock*edge, data = fru, digits = 2, na.rm = TRUE)
tb1b <- sts%>%
merge(., mc) %>%
mutate(Variable = "Fruit length (mm)") %>%
dplyr::select(Variable, stock, edge, mean, sd, min, max, group) %>%
rename(Rootstock = stock,
Interstock = edge,
Sig = group)
sts <- Summarize(diameter_average ~ stock*edge, data = fru, digits = 2, na.rm = TRUE)
tb1c <- sts%>%
merge(., mc) %>%
mutate(Variable = "Fruit diameter (mm)") %>%
dplyr::select(Variable, stock, edge, mean, sd, min, max, group) %>%
rename(Rootstock = stock,
Interstock = edge,
Sig = group)
tb1 <- bind_rows(tb1a, tb1b, tb1c)
tb1 %>% kable(align = 'c')| Variable | Rootstock | Interstock | mean | sd | min | max | Sig |
|---|---|---|---|---|---|---|---|
| Fruit Weigth (g) | CHATO | CHATO | 452.53 | 79.92 | 305.0 | 639.0 | a |
| Fruit Weigth (g) | CHATO | CHULUCANAS | 462.34 | 69.82 | 340.0 | 620.0 | a |
| Fruit Weigth (g) | CHATO | IRWIN | 482.03 | 87.30 | 350.0 | 700.0 | a |
| Fruit Weigth (g) | CHATO | JULIE | 465.97 | 92.07 | 300.0 | 645.0 | a |
| Fruit Weigth (g) | CHULUCANAS | CHATO | 484.97 | 101.98 | 316.0 | 765.0 | a |
| Fruit Weigth (g) | CHULUCANAS | CHULUCANAS | 468.17 | 118.73 | 230.0 | 665.0 | a |
| Fruit Weigth (g) | CHULUCANAS | IRWIN | 447.23 | 70.09 | 310.0 | 605.0 | a |
| Fruit Weigth (g) | CHULUCANAS | JULIE | 484.70 | 93.46 | 367.0 | 717.0 | a |
| Fruit length (mm) | CHATO | CHATO | 105.97 | 6.78 | 93.0 | 120.0 | a |
| Fruit length (mm) | CHATO | CHULUCANAS | 106.28 | 6.80 | 94.0 | 119.0 | a |
| Fruit length (mm) | CHATO | IRWIN | 106.07 | 6.47 | 95.0 | 124.0 | a |
| Fruit length (mm) | CHATO | JULIE | 107.67 | 7.54 | 91.0 | 120.0 | a |
| Fruit length (mm) | CHULUCANAS | CHATO | 106.53 | 7.21 | 95.0 | 123.0 | a |
| Fruit length (mm) | CHULUCANAS | CHULUCANAS | 106.20 | 10.87 | 86.0 | 126.0 | a |
| Fruit length (mm) | CHULUCANAS | IRWIN | 106.43 | 7.28 | 92.0 | 122.0 | a |
| Fruit length (mm) | CHULUCANAS | JULIE | 109.73 | 8.03 | 98.0 | 129.0 | a |
| Fruit diameter (mm) | CHATO | CHATO | 85.23 | 4.72 | 76.0 | 97.5 | a |
| Fruit diameter (mm) | CHATO | CHULUCANAS | 86.09 | 3.61 | 78.5 | 93.5 | a |
| Fruit diameter (mm) | CHATO | IRWIN | 87.63 | 5.07 | 79.5 | 100.0 | a |
| Fruit diameter (mm) | CHATO | JULIE | 86.23 | 5.56 | 75.5 | 97.5 | a |
| Fruit diameter (mm) | CHULUCANAS | CHATO | 87.70 | 5.40 | 78.0 | 100.5 | a |
| Fruit diameter (mm) | CHULUCANAS | CHULUCANAS | 86.08 | 6.61 | 69.5 | 99.0 | a |
| Fruit diameter (mm) | CHULUCANAS | IRWIN | 84.53 | 4.03 | 77.5 | 92.5 | a |
| Fruit diameter (mm) | CHULUCANAS | JULIE | 86.30 | 4.68 | 79.5 | 97.0 | a |
tb1 %>%
write_sheet(ss = gs, sheet = "tb1")5.2.5 Multivariate
Principal Component Analysis (PCA) of fruit biometrics in the mango crop based on the use of rootstock-interstock combinations.
mv <- fru %>%
group_by(stock, edge) %>%
summarise(across(where(is.numeric), ~ mean(., na.rm = T))) %>%
dplyr::select(!c(diameter_1, diameter_2, n_fruits)) %>%
unite("treat", stock:edge, sep = "-") %>%
rename(Treat = treat
, Weight = weigth
, Length = long
, Diameter = diameter_average)
pca <- mv %>%
PCA(scale.unit = T, quali.sup = 1, graph = F)
# summary
summary(pca, nbelements = Inf, nb.dec = 2)
##
## Call:
## PCA(X = ., scale.unit = T, quali.sup = 1, graph = F)
##
##
## Eigenvalues
## Dim.1 Dim.2 Dim.3
## Variance 2.01 0.97 0.02
## % of var. 66.97 32.23 0.79
## Cumulative % of var. 66.97 99.21 100.00
##
## Individuals
## Dist Dim.1 ctr cos2 Dim.2 ctr cos2 Dim.3
## 1 | 1.71 | -1.70 17.91 0.98 | -0.22 0.60 0.02 | -0.01
## 2 | 0.68 | -0.56 1.99 0.69 | -0.37 1.76 0.29 | 0.09
## 3 | 1.85 | 1.38 11.78 0.56 | -1.23 19.60 0.44 | 0.00
## 4 | 0.70 | 0.09 0.05 0.02 | 0.61 4.83 0.76 | 0.33
## 5 | 1.93 | 1.70 17.92 0.78 | -0.91 10.79 0.22 | 0.00
## 6 | 0.57 | -0.29 0.51 0.25 | -0.44 2.46 0.58 | -0.23
## 7 | 2.33 | -2.29 32.54 0.96 | 0.45 2.60 0.04 | -0.06
## 8 | 2.69 | 1.67 17.30 0.38 | 2.11 57.36 0.61 | -0.12
## ctr cos2
## 1 0.03 0.00 |
## 2 4.74 0.02 |
## 3 0.00 0.00 |
## 4 57.67 0.22 |
## 5 0.00 0.00 |
## 6 28.15 0.16 |
## 7 2.18 0.00 |
## 8 7.23 0.00 |
##
## Variables
## Dim.1 ctr cos2 Dim.2 ctr cos2 Dim.3 ctr
## Weight | 0.99 49.14 0.99 | -0.03 0.07 0.00 | -0.11 50.79
## Length | 0.46 10.55 0.21 | 0.89 81.29 0.79 | 0.04 8.16
## Diameter | 0.90 40.32 0.81 | -0.42 18.64 0.18 | 0.10 41.05
## cos2
## Weight 0.01 |
## Length 0.00 |
## Diameter 0.01 |
##
## Supplementary categories
## Dist Dim.1 cos2 v.test Dim.2 cos2 v.test Dim.3
## CHATO-CHATO | 1.71 | -1.70 0.98 -1.20 | -0.22 0.02 -0.22 | -0.01
## CHATO-CHULUCANAS | 0.68 | -0.56 0.69 -0.40 | -0.37 0.29 -0.38 | 0.09
## CHATO-IRWIN | 1.85 | 1.38 0.56 0.97 | -1.23 0.44 -1.25 | 0.00
## CHATO-JULIE | 0.70 | 0.09 0.02 0.07 | 0.61 0.76 0.62 | 0.33
## CHULUCANAS-CHATO | 1.93 | 1.70 0.78 1.20 | -0.91 0.22 -0.93 | 0.00
## CHULUCANAS-CHULUCANAS | 0.57 | -0.29 0.25 -0.20 | -0.44 0.58 -0.44 | -0.23
## CHULUCANAS-IRWIN | 2.33 | -2.29 0.96 -1.61 | 0.45 0.04 0.46 | -0.06
## CHULUCANAS-JULIE | 2.69 | 1.67 0.38 1.18 | 2.11 0.61 2.14 | -0.12
## cos2 v.test
## CHATO-CHATO 0.00 -0.05 |
## CHATO-CHULUCANAS 0.02 0.62 |
## CHATO-IRWIN 0.00 -0.02 |
## CHATO-JULIE 0.22 2.15 |
## CHULUCANAS-CHATO 0.00 -0.02 |
## CHULUCANAS-CHULUCANAS 0.16 -1.50 |
## CHULUCANAS-IRWIN 0.00 -0.42 |
## CHULUCANAS-JULIE 0.00 -0.76 |
f3a <- plot.PCA(x = pca, choix = "var"
, cex=0.8
)
f3b <- plot.PCA(x = pca, choix = "ind"
, habillage = 1
, invisible = c("ind")
, cex=0.8
) 5.2.6 Figure 5
Principal Component Analysis (PCA).
fig <- list(f3a, f3b) %>%
plot_grid(plotlist = ., ncol = 2, nrow = 1
, labels = "auto"
, rel_widths = c(1, 1.5)
)
fig %>%
ggsave2(plot = ., "submission/Figure_5.jpg", units = "cm"
, width = 25, height = 10
)
fig %>%
ggsave2(plot = ., "submission/Figure_5.eps", units = "cm"
, width = 25, height = 10
)
knitr::include_graphics("submission/Figure_5.jpg")5.2.7 Supplementary Figure 2
Results of the contributions and correlation of the variables in the Principal Component Analysis (PCA).
var <- get_pca_var(pca)
pt1 <- fviz_eig(pca,
addlabels=TRUE,
hjust = 0.05,
barfill="white",
barcolor ="darkblue",
linecolor = "white") +
ylim(0, 80) +
labs(
title = "PCA - percentage of explained variances",
y = "Variance (%)") +
theme_minimal()
pt2 <- fviz_contrib(pca,
choice = "var",
axes = 1,
top = 10,
fill="white",
color ="darkblue",
sort.val = "desc") +
ylim(0, 60) +
labs(title = "Dim 1 - variables contribution")
pt3 <- fviz_contrib(pca,
choice = "var",
axes = 2,
top = 10,
fill="white",
color ="darkblue",
sort.val = "desc") +
ylim(0, 100) +
labs(title = "Dim 2 - variables contribution")
pt4 <- ~ {
corrplot(var$cor,
method="number",
tl.col="black",
tl.srt=45,
)
}
plot <- list(pt1, pt2, pt3) %>%
plot_grid(plotlist = ., ncol = 1, labels = "auto") %>%
list(., pt4) %>%
plot_grid(plotlist = ., ncol = 2, labels = c("", "d"))
ggsave2(plot = plot, "submission/FigS2.jpg", height = 20, width = 30, units = "cm")
ggsave2(plot = plot, "submission/FigS2.eps", height = 20, width = 30, units = "cm")
knitr::include_graphics("submission/FigS2.jpg")